mapr
pre - built, certified container images for connecting to all mapr services: mapr - fs, mapr - db, and mapr streams .
mapr provides security controls to ensure that sensitive data is accessible only by authorized users. mapr provides :
the mapr distribution provides a full hadoop stack that includes the mapr file system (mapr - fs), mapreduce, a complete hadoop ecosystem, and the mapr control system user interface. you can use mapr with apache hadoop, hdfs, and mapreduce apis
developers that are using containers can take advantage of the mapr persistent application client container (pacc) for access to persistent data in mapr. mapr paccs are pre - built, certified container images that can be used for container applications to securely connect to and access data from all mapr platform services (mapr - fs, mapr - db, mapr streams). key benefits include :
this is documentation for mapr version 5. 0. you can also refer to mapr documentation for the latest release .
the mapr converged community edition is available free of cost with usage restrictions specified in the mapr end user license agreement, and with community forum support. read more: the mapr converged community edition licensing information: mapr end user license agreement
mapr platform bundle enterprise premier for hard disk drives (hdd) and solid state drives (ssd). subscription includes mapr - xd enterprise premier hdd, mapr analytics with hadoop enterprise premier, mapr advanced analytics with spark enterprise premier, mapr interactive sql engine with drill enterprise premier, mapr document database enterprise premier, and mapr event data streams enterprise premier. these products may be deployed to servers as needed for one production cluster and one development cluster, each managed by mapr - xd enterprise premier .
post! here' s a quick summary of the new features of mapr - db and mapr - es which shows some of the enhancements for developers: mapr 6. 1 simplifies the development of
in addition to mapr - xd enterprise premier and mapr analytics with hadoop enterprise standard: · mapr - db ojai connector for apache spark. mapr - db binary connector for apache spark orbit cloud suite features: · object connectors to s3, azure blob and swift · rest api
today, mapr announced that it will distribute and support the apache spark platform as part of the mapr distribution for hadoop in partnership with databricks. we’re thrilled to start on this journey with mapr for a multitude of reasons .
products what' s new mapr 6. 1 mapr 6. 1 unveils major data platform updates for ai and analytics new features lower tco and streamline security across on - premises, edge, and cloud deployments. mapr ...
free per restrictions specified in the mapr end user license agreement. read the datasheet
reliable delivery of global, high speed streams of event data with mapr streams .
hbase applications and mapreduce jobs can co - exist on the same nodes without disrupting cluster performance. mapr - db tables support in - memory column families to speed inserts and updates. a mapr cluster supports mixed environments that use mapr - db tables and apache hbase as well as environments that use mapr - db tables exclusively .
mapr snapshots provide complete recovery capabilities. mapr snapshots are rapid point - in - time consistent snapshots for both files and tables. mapr snapshots make efficient use of storage and cpu resources, storing only changes from the point the snapshot is taken. you can configure schedules for mapr snapshots with easy to use but powerful scheduling tools .
mapr - db and mapr streams deliver immediate updates to remote replicas in real time to enable very low rpos. replicas are immediately available for active use upon failover .
mapr - edge is a small footprint edition of the mapr converged data platform that addresses the need to capture, process, and analyze iot data close to the source .
mapr platform services are the core data handling capabilities of the mapr converged data platform. modules include mapr - fs, mapr - db, and mapr streams. its enterprise - friendly design provides a familiar set of file and data management services, including a global namespace, high availability, data protection, self - healing clusters, access control, real - time performance, secure multi - tenancy, and management and monitoring .
the edition of mapr that you use determines which features are available on the cluster .
mapr provides developers the widest variety of popular open source projects for developing data applications .
according to allthingsd, mapr raised a $ 30 million series c round in march 2013. the $ 110 million financing would bring mapr’s total funding to approximately $ 170 million .
mapr is a complete enterprise - grade distribution for apache hadoop. the mapr distribution for apache hadoop has been engineered to improve hadoop’s reliability, performance, and ease of use .
a mapr cluster integrates nosql technology that stores tables natively in the filesystem layer. mapr - db tables support the hbase api. the mapr distribution for hadoop integrates files and tables to provide significant performance and administration benefits over other distributions. mapr clusters deliver a 2 - 10x throughput advantage and a 2 - 50x read latency decrease across different workloads compared to other distributions while significantly reducing latency variability. tables stored in the mapr - fs layer benefit from
mapr said in a statement that the new financing will be used to grow mapr’s big data and analytics segment. according to the company, bookings tripled in q1 2014 over 2013 .
mapr has raised $ 110 million in financing to help enterprise customers take advantage of big data .
connect your browser to the link provided by the mapr - setup script and follow the instructions .
but mapr doesn' t want you to think of it as solely a hadoop platform. big on data bro andrew brust previously reported on mapr getting container religion, and then hawking its file system to sap for providing low - cost cloud storage. cue the drum roll: that sets the stage for today' s announcement that mapr is rebranding its file system to mapr - xd .
for authorization, mapr provides access control lists (acls) for job queues, volumes, and the cluster as a whole. because mapr supports posix permissions on files and directories, mapr - fs performs permission checks on each file access. other hadoop distributions only check permissions on file open .
mapr - fs is the enterprise standard posix file system that provides high - performance read / write data storage for the mapr converged data platform. mapr - fs includes important features for production deployments such as fast nfs access, access controls, and transparent data compression at a virtually unlimited scale .
mapr streams is a global publish - subscribe event streaming system for big data. it connects data producers and consumers worldwide in real time, with unlimited scale. mapr streams is built into the mapr converged data platform, making it the only highly available streaming system to support global event replication .
mapr offers enterprise tools based on apache hadoop, an open - source, big - data platform. mapr aims to support hadoop - based projects while offering disaster recovery, security and data protection .
mapr works with customers in financial services, health care, media, retail and telecommunications. on its website, mapr lists samsung, beats music, transunion, cisco and hp among its clients .
governance in the age of big data presents a unique set of challenges that only mapr is equipped to address. by leveraging the mapr dataops governance framework, customers are able to govern all data across the enterprise. mapr also recognizes that governance can be a daunting concept. trained experts from the mapr professional services team are available to guide you along your governance journey through our data governance quick start solution .
mapr provides performance improvements in the shuffle phase of mapreduce and adds high availability for all hadoop services .
mapr gives you real - time capabilities beyond what other platforms can provide in a single cluster. with businesses always seeking to respond faster to new events, mapr provides key real - time capabilities for :
mapr has partnered with datameer, which provides a self - service business intelligence platform that runs best on the mapr distribution for apache hadoop. your download of mapr includes a 30 - day trial version of datameer analytics solution (das), which provides spreadsheet - style analytics, etl and data visualization capabilities .
run setup script on your server. example: $ sudo bash / tmp / mapr - setup. sh
: register for the new
secure a mapr cluster
course today. learn about securing data on a cluster, the four pillars of security, and why you should run a mapr cluster in secure mode .
the mapr converged data platform is available in two editions, each one suited for your specific business needs .
our three platform services— mapr - fs, mapr - db, and mapr streams — are unified by common core capabilities built into the underlying platform such as high availability, real - time access, unified security, multi - tenancy, disaster recovery, a global namespace, self - healing, and management and monitoring .
organizations of all sizes are seeing an increase in audit and compliance demands from regulators and customers. the mapr converged data platform is designed from the ground up to empower mapr customers to be compliant with many of these standards. compliance with standards is just one way that mapr helps customers mitigate risk around today’s security threats and breaches .
immediate access to large data files in mapr - fs, even as they are being loaded into the system .
flexibility in deployment, capable of being deployed on mapr nodes or remote nodes, including nodes in the cloud .
the design of the patented mapr converged data platform speaks directly to enterprise architects who know best that architecture matters .
mapr uses customized units of i / o, chunking, resync, and administration. these architectural elements allow mapr clusters to run at speeds close to the maximum allowed by the underlying hardware. in addition, the directshuffle technology leverages the performance advantages of mapr - fs to deliver strong cluster performance, and direct access nfs simplifies data ingestion and access. mapr - db tables, available with the m7 license, are natively stored in the file system and support the apache hbase api. mapr - db tables provide the fastest and easiest to administer nosql solution on hadoop .
while mapr' s open core strategy is no longer an outlier in the hadoop ecosystem, its converged platform remains unique. while there remain gaps with regard to data governance, mapr could have a strong tco story to tell .
mapr leverages the hadoop fair scheduler to ensure fair allocation of resources to different users, and includes support for selinux .
mapr delivers a powerful node recovery process via patented innovations. mapr serves your big data environments that cannot lose data, must run on a 24x7 basis, and require immediate recovery from node and site failures—all with a smaller data center footprint. mapr supports these capabilities for the broadest set of applications from batch analytics to interactive querying and real - time streaming .
mapr provides complete random read - write capable, posix compliant, highly available, high performance nfs access for production use .
mapr converged data platform for docker supports containerization of existing and new applications by providing containers with persistent data access from anywhere .
the mapr distribution for hadoop provides high availability for the hadoop components in the stack. mapr clusters don’t use namenodes and provide stateful high - availability for the mapreduce jobtracker and direct access nfs. works out of the box with no special configuration required .
mapr provides high availability management and data processing services for automatic continuity throughout the cluster. you can use the mapr control system, command - line interface, or rest api to start, stop, and monitor services at the node or cluster level .
the 3. 1 release of the mapr distribution for hadoop provides authentication, authorization, and encryption services to protect the data in your cluster. mapr leverages linux pluggable authentication modules (pam) to support the main authentication protocols out of the box. a mapr cluster can authenticate users through kerberos, ldap / ad, nis, or any other service that has a pam module .
organizations that need to capture, process, and analyze iot data close to the source can take advantage of mapr edge. mapr edge is a small footprint edition of the mapr converged data platform providing secure local processing, quick aggregation of insights on a global basis, and the ability to push intelligence back to the edge for faster and more significant business impact. key capabilities include :
mapr uncovers the significance of the ucs s - series, including what it means for their customers and their partnership with cisco .
in 2013, mapr broke the record for minutesort, a standard benchmark test that measures how much data a system can sort in one minute. mapr was able to sort 15 billion 100 - byte records totaling 1. 5 terabytes of data in 59 seconds .
mapr helps companies around the world deploy hadoop rapidly and reliably, generating significant business results, ” said gene frantz, general partner at google capital. “we led this round of funding because we believe mapr has a great solution for enterprise customers, and they’ve built a strong and growing business. ” mapr announced that frantz will join the company’s board of directors as part of this investment .
while mapr initially supported its own proprietary implementation of hbase that eliminated region servers and the need for compaction operations, it again added its own alternative, mapr - db, which it claims offers higher reliability over hbase; scalability than mongodb; and consistency over cassandra .
when applications go from idea to reality, mapr provides the only production - ready platform for hadoop, spark, and related technologies .
mapr has also tilted at windmills when it comes to distributed pubsub message queuing. while apache kafka has drawn wide scale third party support from data platforms and streaming engine providers alike, mapr introduced its own alternative, mapr streams, which also resides on the same cluster where the file system and nosql databases live. by contrast, kafka would require a separate cluster. strike another blow for flattened architecture .
its rebel stance has meant that mapr must prove its innocence. its underlying components are different from the core apache hadoop stack. but at api level, they are compatible, meaning you can move files between mapr and rival hadoop platforms and run the same spark jobs .
a remote client can easily mount a mapr cluster over nfs to move data to and from the cluster. application servers can write log ﬁles and other data directly to the mapr cluster’s storage layer instead of caching the data on an external direct or network - attached storage .
what' s new in mapr 6. 0? products what' s new? 6. 0 mapr 6. 0 powers dataops, helping you unleash greater value from all your data in less time. the data struggle is real. last generation and even ...
mapr platform services support distinct global cluster deployments that run as a single logical, global cluster. with global namespace support, you can :
the mapr converged data platform is available in two editions - the converged community edition, for free use per restrictions specified in the mapr end user license agreement (eula), and the converged enterprise edition, for critical deployments requiring business continuity. click here to compare our editions .
mapr, a company that prides itself on having built an industrial - grade version of hadoop tuned for high availability and data protection, has closed a $ 30 million series c round of venture capital funding led by the mayfield fund. prior investors lightspeed venture partners, nea and redpoint ventures also participated. the round brings mapr’s total funding raised to $ 59 million. allthingsd reported on mapr’s $ 20 million b round in 2011 .
the mapr platform provides features to logically partition a physical cluster to provide separate administrative control, data placement, job execution, and network access .
mapr snapshots provide protection without duplicating the data. you can take a snapshot of a 1 pb cluster in seconds with no additional data storage .
don' t have servers? mapr can easily be deployed on azure, google cloud platform, amazon web services as well as on centurylink .
you typically need to run hadoop alongside other modern technologies like nosql databases and event streaming systems. with mapr, convergence gives you real - time data access no matter how the data is delivered and stored. mapr delivers scalable, enterprise grade processing across files, tables and streams with :
mapr has rebranded its file system to target the cloud storage business. it' s part of an ongoing strategy to transcend its hadoop heritage .
mapr - xd extends on the core nfs / posix - compliant interface of mapr - fs by adding a new object interface to amazon s3 cloud storage. the target use case is classic data tiering, but extended to the cloud, in this case, colder data is moved to s3 but is managed as a logical single view from mapr - xd. specifically, the file system metadata remains the same, as are security policies .
“hadoop is a cornerstone for the big data ecosystem, and mapr has demonstrated its leadership in the space, ” said albert wang, director at qualcomm ventures. “we invested in mapr because of the strength of its technology in leveraging the expanding internet of things and providing immediate business benefits .
the mapr filesystem, or mapr - fs, is a random read - write distributed file system that allows applications to concurrently read and write directly to disk. the hadoop distributed file system (hdfs), by contrast, has append - only writes and can only read from closed files .
mapr packages a broad set of apache open source ecosystem projects that enable big data applications. the goal is to provide an open platform that lets you choose the right tool for the job. mapr tests and integrates open source ecosystem projects such as hive™, pig™, apache™ hbase™ and mahout, among others. mapr is the only hadoop vendor that supports multiple versions of key apache projects so you can update your environment at your own pace .
tcs and mapr are developing turn - key solutions to address key big data challenges, such as recommendation engines, supply chain optimization and pricing analytics .
the mapr control system (mcs) provides a graphical control panel for cluster administration with all the functionality of the command - line or rest apis .
in addition to the growth capital funding, mapr also raised a $ 30 million debt facility led by silicon valley bank. the deals bring mapr’s total resources raised to date to $ 174 million. its most recent round was a $ 30 million series c led by mayfield announced about 15 months ago .
mapr - db is an enterprise - grade, high performance nosql database management system. it is used to add real - time, operational analytics capabilities to applications built to handle big data. because it is part of the mapr converged data platform, it inherits all the advantages of the underlying platform .
one of the key developer benefits of the mapr converged data platform is its basis on well - known, open apis and interfaces. this enables commercial software vendors such as sap, sas, hp, and cisco to easily deploy large scale applications onto the mapr platform. it also means that even small teams of developers can create enterprise - grade software products by exploiting the built - in protections of the mapr platform as well as mature commercial processing engines .
aside from its contributions to hadoop projects, mapr is significant because of its partnerships with other leading technology companies. for example, mapr' s hadoop distribution is integrated with the google compute engine framework, making it accessible through google' s cloud infrastructure. the mapr hadoop distribution is also an option within the amazon elastic mapreduce service, allowing customers to provision hadoop clusters through the service, and has built - in support for the hp vertica analytics platform .
the storage system architecture used by mapr - fs is written in c / c + + and prevents locking contention, eliminating performance impact from java garbage collection .
mapr data technologies is a visionary silicon valley enterprise software company that pioneered one platform for all data across every cloud. this approach is the industry’s first modern data system. at the core is the mapr converged data platform that enables simultaneous analytics and applications as data happens for companies to create new, intelligent and modern applications .
one of our primary goals at databricks is to drive broad adoption of spark and ensure everybody who uses it has a fantastic experience. this partnership will enable all of mapr’s enterprise customers, existing and new, to leverage spark with the backing of the same great enterprise support available for the rest of mapr’s hadoop distribution. as tomer mentioned in his blog post, spark is one of the most common topics in discussions with mapr’s existing customers and many are even already running it in production !
mapr data fabric for kubernetes scalable, secure, high - performance storage for stateful containerized applications download solution brief solutions data fabric kubernetes the stateful container challenge ...
the architectural advantages of the mapr platform show cost differences of 20 - 50% in terms of total cost of ownership (tco) across capital and operational expenses .
and being a rebel, sometimes there limits to the advantages of thinking different. take kafka: with growing third party support, will mapr streams be left at the altar? of course, you can run mapr with a separate kafka cluster, but then you' ve lost part of the advantage of having that converged platform .
ubiquitous high availability capabilities with jobtracker ha, resourcemanager ha (yarn), file system metadata, and instant recovery (for mapr - db converged enterprise edition) .
the mapr direct access file system enables real - time read / write data ﬂows using the network file system (nfs) protocol. standard applications and tools can directly access the mapr - fs storage layer using nfs. legacy systems can access data and traditional file i / o operations work as expected in a conventional unix file system .
with multi - tenancy, a capability unique to mapr, you can manage distinct user groups, data sets, and applications in a single cluster while keeping them isolated from each other. you can run different jobs at the same time safely, securely, and efficiently. several features contribute to the multi - tenancy capability in mapr :
mapr clusters also incorporate wire - level security (wls) to encrypt data transmission for traffic within the cluster, as well as traffic between the cluster and client machines .
under the final rule, lenders may not exceed a 36 percent military annual percentage rate (mapr), which is calculated to include application, participation, annual and other fees that aren’t considered finance charges under regulation z. the mapr calculation also includes fees and premiums for credit insurance, debt cancellation and debt suspension fees for credit - related ancillary products. however, certain payday alternative loans offered by credit unions pursuant to the national credit union administration rules are eligible for exclusion of application fees from the mapr calculation .
mapr - db is a high - performance nosql database for global data - intensive applications built into the mapr converged data platform. it is a scalable multi - model database that brings together operational applications, analytical applications, real - time streaming, and other workloads to enable next - generation user experiences and business processes. read the executive perspective .
the mapr control system (mcs) is a world - class management solution for administering the mapr converged data platform and related cluster infrastructure through a simple, intuitive, and actionable interface. with built - in real - time insights and faster time - to - action, mcs lowers your opex and is a vital component in the dataops movement .
hadoop is built to process large amounts of data from terabytes to petabytes, and beyond. it delivers greater business impact when used as part of the mapr converged data platform. the mapr platform combines operational and analytical workloads that drive business insights in real time that are not feasible in other environments that suffer from complex integrations between disparate data silos .
mapr streams is a global publish - subscribe event streaming system for big data. it is the only big data streaming system to support global event replication reliably at iot scale .
mapr provides business continuity and disaster recovery services out of the box with mirroring that’s simple to configure and makes efficient use of your cluster’s storage, cpu, and bandwidth resources .
on 7 / 12 at 10: 00 am pst to learn how using nfs and vips with the mapr file system allows you to do more with your data. register now at
mapr is a software company that has been one of the principal contributors to several open - source hadoop projects, including apache hbase, apache hive, apache zookeeper and apache pig .
the mapr converged data platform integrates hadoop, spark, and apache drill with real - time database capabilities, global event streaming, and scalable enterprise storage to power a new generation of big data applications. the mapr platform delivers enterprise grade security, reliability, and real - time performance while dramatically lowering both hardware and operational costs of your most important applications and data .
mapr' s message, then and now, is that open source technology is not always sufficient for making it the last mile to enterprise grade. its strategy is not all that unusual - - it' s the embodiment of open core, where you supplement open source technology with proprietary value - add. it began with a shot across the bow to one of apace hadoop' s pillars - - the file system, which was replaced by mapr' s own (mapr - fs), providing the update and delete capabilities that hdfs lacked .
the final rule also includes various disclosure requirements, including an mapr description (without the requirement to disclose the numerical mapr as a percentage), disclosures required by regulation z and a clear description of the payment obligation. for closed - end credit, a payment schedule could suffice. the disclosures must be provided in writing before or at the time the borrower becomes obligated on the transaction or establishes a consumer credit account. in addition, the mapr and payment obligation must be provided orally. a toll - free number may be used for this purpose .
mapr is led by a successful, seasoned executive team, and is well - funded by top venture capital firms. just ask google, who led a round of $ 110 million .
· global namespace · compression · unified security · multi - tenancy · quotas · trillions of files · data topologies · cloud scale resiliency · built - in file system · self - healing · data protection replication · auto - balancing · mapr management · mapr monitoring · thousands of volumes available: · cloud - optimized installer for aws and azure. (gce coming soon )
mapr - xd is a highly - scalable converged storage platform for high - volume enterprise storage, in - place analytics of unstructured data, and archival and protection of critical data. mapr - xd bridges the gap between traditional and new - age applications, and serves as the foundation for your data fabric across edge, on - premises, and cloud. read the executive perspective .
there’s no limit to the number of tables or files you can have in a mapr cluster. tables can be managed by individual users, freeing cluster administrators from database administration overhead. with mapr - db tables, cluster administrators do not have to manage regionservers or daemons, and region splits are handled automatically. node upgrades and other administrative tasks do not cause downtime for table storage .
eol' s multiple antenna profiler (mapr), generally deployed as part of an iss (integrated sounding system), uses spaced antenna techniques to measure high time resolution wind profiles as short as 30 seconds compared with 15 minutes or longer from traditional profiling techniques. mapr is well suited to study air motion around frontal boundaries and other small - scale features and precipitation particle dynamics .
mapr is one of three companies that has made a name for itself by building a business around hadoop, the open - source technology that aims to help companies analyze big data and analytics questions to increase profits or reduce costs. mapr, which competes with both cloudera and hortonworks, prides itself on having built an industrial - grade version of hadoop tuned for high availability and data protection .
there' s still a major gap that mapr has yet to fill - - its rivals, cloudera and hortonworks have been far more proactive with data governance and security. while its converged platform offers a common target for third party offers to encrypt or protect data, mapr has yet to provide its own solutions for data discovery, audit, lineage, metadata management, and policy enforcement .
it brands its product as a converged data platform that, in effect, flattens the lambda architecture by supporting streaming, interactive, and batch processing on the same cluster. the company emphasizes that its platform is not disparate pieces, but file, table, and streaming engines springing out of common building blocks. that encompasses the nfs, posix - compliant mapr - fs file system on which its nosql database (mapr - db) tables co - reside. and with the open source drill project that mapr leads, you can use the same query engine to target sql and json data .
mapr has been working hard for many years to make dataops more effective. the way we did that is with a very innovative technology platform that really thought about the comprehensive needs of the dataops community .
mapr supports dozens of open source projects and is committed to using industry - standard apis to provide a frictionless method of developing and deploying exciting new applications that can meet the most stringent production runtime requirements .
with mapr, you can configure hadoop services to run on multiple nodes for failover. if one service node fails, another continues to perform the tasks related to that service without delaying the mapreduce job .
in the hadoop world, we' ve noted that mapr has always marched to a different drummer. its core file system is the building block for its converged platform, where you can squash the lambda architecture, running batch, interactive, and real - time on the same cluster. putting iot money where its mouth its, mapr also recently added edge processing to extend the footprint of its converged platform .
“our partnership with mapr in the big data space is already delivering measurable business benefits for customers and we look forward to expanding this alliance to jointly pursue other opportunities where we have deep expertise, ” said ramaswamy .
the shuffle phase of a mapreduce job combines the map output so that all the records from a given key / value pair’s key go to one reduce task. this phase involves a great deal of copying and coordination between nodes in the cluster. shuffling in mapr - fs is much faster than other hadoop distributions because mapr uses highly optimized, efficient remote procedure call connections to transport data while other hadoop distributions use http connections .
other hadoop distributions keep map output on local disk, which creates competition for disk space between local and distributed storage. in mapr, any spilled data is stored in the distributed file system making it directly accessible .
tata consultancy services, the country’s largest it company, today said it has partnered with mapr technologies to make new big data offerings to enterprise customers which will allow them to easily and rapidly capture value from big data .
the mapr distribution for hadoop provides built - in mirroring to set recovery time objectives and automatically mirror data for backup. you can create local or remote mirror volumes to mirror data between clusters, data centers, or between on - premise and public cloud infrastructures. mirror volumes are read - only copies of a source volume. you can control the schedule for mirror refreshes from the mapr control system or with the command - line tools .
mapr analytics and ml engines include all of the tools needed to conduct real - time analytics and machine learning at scale, backed by the industry & apos; s only platform that integrates files, tables, and streams .
and so, given the theme of convergence, it' s not surprising that mapr also boasts of bringing analytic and operational processing together. yes, they run on the same cluster, but not the same storage engines; analytics is still the domain of the hadoop file system side, while operational is confined to the nosql database - - although you could use drill query across both. mapr' s narrative of bringing analytics and operational applications together is not unusual .
mapr just concluded its first - ever analyst event, a milestone for a company that has traditionally operated well below the radar. it has clawed out a foothold where 40 percent of its customer base was poached from cloudera and hortonworks, and where it has achieved a 99 percent renewal rate for subscriptions that typically grow 35 percent from year to year. like cloudera, mapr has predicted that it would go cash flow neutral by 2017 - 18, with implications of looming ipo .
the built - in mapr high availability (ha) features eliminate single points of failure at the node, and include file system metadata, nfs access, resource management (yarn), and job tracking levels. you can benefit from :
when choosing a hadoop vendor, you want options. you want to choose the right tool for the job, as well as the right time to upgrade. mapr gives you multiple choices for key capabilities, as well as support for multiple project versions .
what sets us apart? simply put, the folks who choose to work at mapr enjoy working on cutting - edge, challenging projects. we set the bar high here, because we’re constantly inspired by both the technology we’re working on and the people we work with. at mapr, it’s not just about the perks. it’s about working on game - changing technology with some of the best and brightest people in the world. we’re at the forefront of redefining enterprise computing, and we have fun doing it .
covering data platforms, one has to have enough knowledge about storage to be dangerous. as mapr added the option for selling its storage system a la carte, our initial thought was, why enter a mature space already dominated by household names? while mapr' s file system share the same posix - compliance as emc, netapp and other enterprise storage stalwarts, it is positioning its offering as a lower priced alternative taking advantage of modern, commodity scale - out hardware. well, that makes it look a bit like emc isilon .
the industry’s leading unified data platform, the mapr converged data platform is able to simultaneously do analytics and applications with speed, scale, and reliability. it converges all data into a data fabric that can store, manage, process, apply, and analyze as data happens .
mapr - es is a global publish - subscribe event streaming system for big data. it is the first big data scale streaming system built into a converged data platform and the only big data streaming system to support infinite data persistence and global event replication reliably at iot scale .
where do i start? top of the class technologies, tremendous opportunities to learn beyond your job role, colleagues that you truly admire. but what sets mapr truly apart from the rest is that the lost art of mentoring is very much alive within its walls .
bright and talented people are what make mapr special and i love that i get to hire people to add to that. we work in one of the hottest areas of technology - and we work hard - but we also have a lot of fun doing it .
mapr also makes the case that converged platforms are more efficient for iot as well, because it means less roundtrips to different clusters for aggregating, streaming, parsing, analyzing, and persisting the data. but convergence for use cases as distributed as iot only go so far, literally, as the dispersed nature of iot data and bandwidth limitations augur for filtering, pre - processing and aggregation out at the edges. the question is whether mapr will follow in amazon' s footsteps in offering a greengrass - like pre - processing facility out at the edge .
nonetheless, there are limits to the degree that mapr can tout advantages like high performance or convergence. in an era of spark (which mapr supports), real - time performance on hadoop not so unusual. and the advantages of a converged platform may not suit all scenarios. no matter how performant your platform, if you have highly demanding dueling workloads, such as highly complex batch jobs involving tens of petabytes of data running alongside real - time, continuous iot applications running a smart city, it may still be advantageous to run them on separate clusters .
mapr 6. 0 powers dataops, helping you unleash greater value from all your data in less time. the data struggle is real. last - generation and even newer technologies are limiting and lead to silos across the organization, which hinder innovation, collaboration, and access to data .
with mapr orbit cloud suite our vision is to empower you to unleash your full cloud potential wherever you are in your cloud journey. we do this with unique value - add capabilities across all cloud operating models including: private cloud, public cloud, multi - cloud, and edge .
cisco it built a big data platform to transform data management and provide big data analytics services to cisco business teams. cisco used mapr for their enterprise hadoop architecture to unlock hidden business intelligence of their globally distributed large data sets, while also providing service - level agreements (slas) for internal customers .
the mapr converged data platform enables direct processing of files, tables, and event streams. unlike
connected
environments that require complex integrations and orchestration, convergence offers a streamlined architecture that enables real - time insights, a consistent security framework across compute engines, higher resource utilization, and reduced administrative overhead .
at databricks we are fully committed to open source, and we’re excited to partner with mapr - a company with strong support for open source big data projects - to together help drive continued growth and innovation of spark. join us at the upcoming spark summit, the largest conference focused on spark, to learn more !
by using mapr, comscore is able to easily manage and significantly scale their hadoop cluster, create more files faster, process more data faster, and produce better streaming and random i / o results than other hadoop distributions – and do so confidently knowing they can count on data protection and disaster recovery functions when needed .
mapr says it has 500 paying licensees and that bookings in the first quarter of 2014 were triple those seen in the prior year. (but as is typical with startups, it doesn’t disclose those figures .) the company says it plans to use the new funding to boost its global go - to - market efforts .
mapr has made considerable headway with customers like american express that required the type of analytic performance of spark - - about five years before spark emerged. it also required the ability to update files in place, but commercial file systems like isilon at the time weren' t equipped for handling large - scale parallel data access .
in your business - critical big data environments, reliability, security, multi - tenancy, and speed are all important components. mapr customers achieve 99. 999% uptime and no data loss on a broad collection of distinct data sets, all while getting more output from fewer resources to lower their total cost of ownership (tco) .
you can manage volume permissions through access control lists (acls) in the mapr control system or from the command line. you can also set read, write, and execute permissions on a file or directory for users and groups with standard unix commands, when that volume has been mounted through nfs, or using standard hadoop fs commands .
but then again, mapr is positioning this for cloud storage - it' s not trying to replace on premise enterprise storage, . but then again, for truly scalable storage, object stores such as s3, azure blob storage, google cloud storage are the default. incumbents like dell emc are also trying to home in on the action .
in addition to mapr - xd enterprise standard · basic posix client · container client (pacc) · adv. data protection with instant snapshots · disaster recovery with multi - site mirroring · multi tenancy protection · cloud file migration · snapshots orbit cloud suite features: · multi - site mirroring (across edge, multiple clouds and on - premises )
increasingly, mapr, the rebel has gone mainstream, but not necessarily by joining the crowd. instead, the rest of the industry ended up embracing the same open core model, but with their own twists on implementing it. cloudera has been open core from the start, but unlike mapr, focuses its unique content away from the runtime (e. g. , for monitoring, data governance, sql optimization, and encryption key management). hortonworks, the embodiment of 100 percent open source, has recently taken a more realpolitik strategy that began with several oem agreements with atscale, syncsort, and pivotal followed by a more drastic departure with its special hortonworks data cloud for aws that swaps in amazon s3 cloud storage for hdfs .
to schroeder, that’s a costly model. “our competitors’ model is very cash intensive and you have to wonder whether or not they’ll ever be cash - flow positive, ” he said. “we want to provide our customers with the best technology. ” practically all — 92 percent, schroeder said — of mapr’s customers pay primarily for licenses and not for ancillary services and support .
mapr announced this morning that it had raised $ 110 million in combined equity and debt financing. the $ 80 million equity - bearing portion of the round was led by google capital, the search giant’s growth equity fund, with participation from qualcomm ventures, the investment arm of the wireless chip company. prior investors lightspeed venture partners, mayfield fund, nea and redpoint ventures also participated .
when it emerged from stealth in 2011, mapr was an outlier in the hadoop community. at the time, hadoop was defined largely by two projects adapted from google research: mapreduce, which introduced highly linear, massively parallel processing to big data, and the hdfs file system, which could accommodate data by the petabyte. and at the time, hadoop was defined as an apache open source platform .
the new s3 support from mapr - xd is a response to more tightly interweaving s3 into the online system. traditionally, s3 was the place where cloud data was stored, but when it was consumed by managed hadoop services such as amazon emr, it was marshaled into its own file system. amazon on its own has been exposing s3 data through ad hoc sql query services like athena, and more recently to redshift through spectrum .
and back to our original point: mapr' s practices aren' t all that different from the rest of the field anymore. but forget about acceptance of open core at the moment, the existence of open source or standards won' t guarantee interoperability. for instance, in the hadoop world, there are at least a dozen or more interactive sql engines - - not to mention in the sql relational database world, there' s even more variants floating around .
i talked with ceo john schroeder last week. he told me that about half of mapr’s customers are the traditional web - and cloud - based companies, while the other half are financial and telecommunications and manufacturing companies. “our approach to the market is heavy on investment in research and development, ” he said. the reason? “hadoop is early technology and there are a lot of must - have technologies that hadoop is going to have to add in order to be a real big data platform. ”
the mapr distribution for hadoop provides snapshots, which enable you to roll back to a known good data set. a snapshot is a read - only image of a volume that provides point - in - time recovery. snapshots only store changes to the data stored in the volume, and as a result make extremely efficient use of the cluster’s disk resources. snapshots preserve access to historical data and protect the cluster from user and application errors. you can create a snapshot manually or automate the process with a schedule .
the multiple antennas are used to make a rapid wind measurement using a technique known as spaced antenna winds. as the atmosphere moves over the radar, the motion of atmospheric echoes is tracked over the multiple receiving antennas to make a wind measurement. measurements can be made on time scales of 30 seconds to 5 minutes, which is considerably faster than the 10 - 15 minutes required by traditional dbs wind profilers. mapr can also be run in multiple frequency mode to make rim (range imaging) fine range resolution measurements .
everything is coming up hadoop. another company in the business of selling a version of the open - source big - data platform has landed another round of funding .
its approach is different from the other primary players in the hadoop market. the best known of that set is cloudera, and the second is hortonworks. “hadoop needs a tremendous amount of innovation, ” schroeder says. “it’s really early in the technology cycle. it needs large infusions of focused r & d and development of ip. ”
compare that to cloudera, which announced its own $ 65 million series e round of funding at an implied valuation of $ 700 million, late last year. like linux, the open source operating system that runs on so many servers, hadoop is technically free, and any company can go out and download it for nothing. the trick comes in knowing what to do with it, and managing it, and getting value out of it. cloudera’s primary approach is to sell value - added services around it, and help companies get more out of hadoop than they otherwise would. hortonworks has a similar approach .
instead, the services come from third party systems integrators and accenture and booz allen hamilton. “if you look today, and 24 months down the road, certainly all the systems integrators are expanding and will continue to expand their big data practices. it’s not a great business model as a company to bank on long - term services revenue. i think the route to growing a successful company is around license revenue. ”
mapr technologies is an enterprise software company headquartered in san jose , california . mapr provides an apache hadoop distribution , a distributed file system , database management system , a set of data management tools and other related software . combining analytics in real-time with operational applications , its technology runs on both commodity hardware and public cloud computing services . 
mapr technologies is an enterprise software company headquartered in san jose, california. mapr provides an apache hadoop distribution, a distributed file system, database management system, a set of data management tools and other related software. combining analytics in real-time with operational applications, its technology runs on both commodity hardware and public cloud computing services.
mapr technologies is an enterprise software company headquartered in san jose, california. mapr provides an apache hadoop distribution, a distributed file system, database management system, a set of data management tools and other related software. combining analytics in real-time with operational applications, its technology runs on both commodity hardware and public cloud computing services.