Hadoop

Metanautix Emerges From Stealth With $7M In Series A Funding For Streamlined Big Data Processing And Analytics

Metanautix emerged from stealth today by announcing the finalization of $7M in Series A funding in a round led by Sequoia Capital. Additional investors include the Stanford University endowment fund and Shiva Shivakumar, former VP of Engineering at Google. Metanautix delivers a Big Data analytics platform composed of a SQL interface for querying Hadoop data in conjunction with data discovery functionality that empowers analysts to more easily navigate massive amounts of structured and unstructured data. The platform focuses on simplifying the data pipeline between data acquisition and the production of data analytics. As such, Metanautix removes the necessity of combining disparate data sources and thereby delivers the benefits of distributed computing alongside the simplicity of SQL. Users of Metanautix can perform analytics in parallel on structured and unstructured data by taking advantage of an interface that allows users to understand the topography of the data that they are navigating. Founded by veterans of Google and Facebook, Metanautix intervenes in the big data analytics space by allowing users to run analytics on multiple streams of Big Data as noted by CEO Theo Vassilakis below:

The modern enterprise operates on a plethora of data sources. There is great value in using all of these data sources and in providing superior access to ask questions of any data. We’ve made it fast and simple for anyone in an organization to work with any number of data sources at any scale and at a speed that enables rapid business decisions.

Vassilakis notes the ability of Metanautix to manage “any number” of datasets “at any scale” toward the larger end of delivering actionable business intelligence from disparate data sources. Given Vassilakis’s background at Google working on Dremel and the experience of Metanautix’s CTO Apostolos Lerios with processing frameworks for billions of photographic images during his tenure at Facebook, the industry can expect Metanautix to deliver a truly multivalent processing and analytics engine capable of managing heterogeneous data sources of all kinds. Expect more details about the platform to emerge in forthcoming months but, based on the experience of its founders, the Big Data space should brace for the entry of a disruptive Big Data analytics and processing engine that can deliver analytics on massive datasets by means of a radically streamlined operational process. That said, Metanautix will need to find its niche quickly in order to outshine competitors such as Pivotal and Infochimps, the former of which recently announced a collaboration with Hortonworks to enhance Apache Ambari.

Categories: Big Data, Hadoop, Metanautix, Venture Capital

Pivotal And Hortonworks Collaborate To Advance Apache Ambari For Hadoop Management

Pivotal and Hortonworks will collaborate to accelerate development of Apache Ambari, the open source framework for provisioning, managing and monitoring Hadoop clusters. Pivotal will dedicate engineers toward advancing the “installation, configuration and management capabilities” of Apache Ambari as part of the larger project of contributing to software that promotes adoption of Apache Hadoop. In a blog post, Pivotal’s Jamie Buckley elaborated on the value of Apache Ambari to the Hadoop ecosystem as follows:

Apache Hadoop projects are central to our efforts to drive the most value for the enterprise. An open source, extensible and vendor neutral application to manage services in a standardized way benefits the entire ecosystem. It increases customer agility and reduces operational costs and can ultimately help drive Hadoop adoption.

Here, Buckley remarks on the way in which Ambari enhances the process of deploying and managing Hadoop by reducing costs and increasing the flexibility of customer choices regarding the operationalization of Hadoop. Meanwhile, Shaun Connolly, VP Strategy at Hortonworks, commented on the significance of Pivotal’s contribution to the Apache Ambari project as follows:

Pivotal has a strong record of contribution to open source and has proven their commitment with projects such as Cloud Foundry, Spring, Redis and more. Collaborating with Hortonworks and others in the Apache Hadoop ecosystem to further invest in Apache Ambari as the standard management tool for Hadoop will be quite powerful. Pivotal’s track record in open source overall and the breadth of skills they bring will go a long way towards helping enterprises be successful, faster, with Hadoop.

Connolly highlights Pivotal’s historical commitment to open source projects such as Cloud Foundry and its track record of success helping enterprises effectively utilize Apache Hadoop. Hortonworks stands to gain from Pivotal’s extraordinary engineering talent and reputation for swiftly releasing production-grade code for Big Data management and analytics applications. Meanwhile, Pivotal benefits from enriching an open source project that both vendors refer to in the context of a “standard” management tool for the Apache Hadoop ecosystem. The real winner, however, is Hortonworks, who now can claims the backing of Pivotal for the open source project Ambari incubated by some of its engineers, but also reaps the benefits of dedicated engineering staff from Pivotal that will almost certainly accelerate the rate of development of Ambari. The only qualification, here, is that Pivotal’s collaboration with Hortonworks is likely to ensure the optimization of Ambari for both the Pivotal HD and Hortonworks distribution, with the ancillary consequence that Ambari may be less suited for other Hadoop distributions such as Cloudera and MapR. Regardless, the collaboration between Hortonworks and Pivotal promises to serve as a huge coup for the Big Data industry at large both with respect to expediting development of Apache Ambari, and constituting a model for collaboration between competitors in the Big Data space that will ultimately enhance Hadoop adoption and effective utilization.

Categories: Big Data, Hadoop, Pivotal | Tags:

HP Invests $50M In Hortonworks As Big Data Revolution Accelerates With Gusto

On Thursday, HP announced an agreement to invest $50M in Hortonworks. HP’s investment builds on the $100M Hortonworks raised in March in a financing red led by funds managed by Blackrock and Passport Capital as well as existing investors. The investment illustrates HP’s commitment to its reseller relationship with Hortonworks that allows it to resell the Hortonworks Data Platform. Moreover, HP plans to continue refining the engineering of its products such that they integrate with YARN, the resource management component of version 2.x of Hadoop. In addition to preparing its products to operate in conjunction with YARN, HP will be integrating its product architecture to optimally perform in conjunction with the Hortonworks Data Platform more generally. Key HP products targeted for integration with the Hortonworks Data Platform include the HP HAVEn platform, one component of which is HP Vertica. As a result of the $50M equity investment, HP’s Executive Vice President and Chief Technology Officer Martin Fink will join the board of directors of Hortonworks. HP’s investment in Hortonworks underscores how the Big Data revolution lies poised to accelerate as technology companies deepen their relationships with Hadoop vendors in anticipation of delivering turnkey big data analytics solutions that simplify and streamline the operationalization of Big Data.

Categories: Hadoop, Hortonworks | Tags: ,

Databricks Closes $33M In Series B Funding And Launches Databricks Cloud Powered By Apache Spark

Databricks, the company founded by the team that developed Apache Spark, recently announced the finalization of $33M in Series B funding in a round led by New Enterprise Associates with existing participation from Andreessen Horowitz. The company also revealed plans for commercializing Apache Spark by means of the newly launched Databricks Cloud that simplifies the data pipeline for data storage, ETL processing and thereupon running analytics and data visualizations on cloud-based Big Data. Powered by Apache Spark, the Databricks Cloud leverages Spark’s array of capabilities for operating on Big Data such as its ability to operate on streaming data, perform graph processing, offer SQL on Hadoop as well as its machine learning functionality. The platform aims to deliver a streamlined data pipeline for ingesting, analyzing and visualizing Hadoop-based data in a way that dispels the need to utilize a combination of heterogeneous technologies. Databricks will initially offer the Databricks Cloud on Amazon Web Services but plans to expand its availability to other clouds in subsequent months.

Categories: Big Data, Databricks, Hadoop

MapR Finalizes $110M In Equity And Debt Financing Led By Google Capital And Silicon Valley Bank

On Monday, MapR Technologies announced the finalization of $110M in funding based on $80M in equity financing and $30M in debt financing. Google Capital led the equity funding in collaboration with Qualcomm Incorporated, Lightspeed Venture Partners, Mayfield Fund, NEA and Redpoint Ventures while MapR’s debt funding was financed by Silicon Valley Bank. The funding will be used to spearhead MapR’s explosive growth in the Hadoop distribution and analytics space as illustrated by a threefold increase in bookings in Q1 of 2014 as compared to 2013. Gene Frantz, General Partner at Google Capital, commented on Google Capital’s participation in the June 30 funding raise as follows:

MapR helps companies around the world deploy Hadoop rapidly and reliably, generating significant business results. 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.

Monday’s announcement comes soon after MapR’s news of its support for Apache Hadoop 2.x and YARN in addition to all five components of Apache Spark, the open source technology used for big data applications that specialize in interactive analytics, real-time analytics, machine learning and stream processing. The additional $110M in funding strongly positions MapR with respect to competitors Cloudera and Hortonworks given that Cloudera recently raised $900M and Hortonworks finalized $100M in funding. The news of MapR’s $110M funding also coincides with a recent statement from Hortonworks certifying the compatibility of YARN with Apache Spark as part of a larger announcement about the integration of Spark into the Hortonworks Data Platform (HDP) alongside its Hadoop security acquisition XA Secure and Apache Ambari for the provisioning and management of Hadoop clusters. With a fresh round of capital in the bank and backing from Google, the creators of MapReduce, MapR signals that the battle for Hadoop market share features a three horse race that is almost certain to intensify as vendors compete to streamline and simplify the operationalization of Big Data. In the meantime, Big Data-related venture capital continues to flow like water bursting out of a fire hydrant as the Big Data space tackles problems related to big data analytics, streaming big data and Hadoop security.

Categories: Hadoop, MapR, Venture Capital | Tags: , , ,

Actian Announces “Right To Deploy” Pricing Model Marked By Freedom From Vendor Lock-In For Big Data Analytics

Big data analytics vendor Actian today announced the availability of customer-friendly pricing options that render it easier for customers to take advantage of its analytics platform for Apache Hadoop. Actian’s latest pricing options feature “capacity-based and subscription models” in addition to a Right to Deploy option that confers an expanded range of flexibility regarding deployment options for the Actian Analytics Platform. The Actian Analytics Platform delivers actionable business intelligence and advanced data visualization for Hadoop-based data that takes advantage of the platform’s proprietary predictive analytics algorithms and low latency. Moreover, the Actian Analytics platform’s Hadoop SQL Edition provides a SQL compliant Hadoop analytics platform that allows users to perform data discovery, data profiling and analytics via SQL in contrast to MapReduce. As of today’s announcement, Actian’s Right to Deploy option allows customers unlimited usage of the platform for a period of one, two or three years in addition to the right to use whatever has been deployed, forever. The Right to Deploy choice represents a particularly attractive option for customers that anticipate significant expansions in their business that dictate the need for enhanced infrastructure and application scalability. Moreover, the Right to Deploy option gives customers freedom from vendor lock-in by empowering customers to use their deployments whether they continue to partner with Actian or choose another vendor for their Hadoop analytics needs. Actian’s simplified platform pricing offers some of the greatest flexibility regarding Big Data analytics in the industry, in a red hot space marked by an increasing number of vendors large and small. That said, few vendors have streamlined and simplified the process of operationalizing Big Data analytics in a way that lays out programmatic approaches to obtaining meaningful analytics on Hadoop that vary in conjunction with the specific use case in mind. Expect increasing competition in the Hadoop analytics space to drive more and more vendors to differentiate themselves from the pack, although the main task, for the industry at large, consists of delivering a turnkey solution for big data analytics featuring machine learning-based, best practice recommendations for extracting meaningful analytics from massive, ever increasing amounts of data.

Categories: Actian, Big Data, Hadoop | Tags: ,

Hortonworks Announces Readiness Of YARN For Apache Spark

On Thursday, Hortonworks announced that Apache Spark is “YARN Ready” and compatible with the multiple workloads and additional CPU processing-demands specific to Spark applications. As a result of the compatibility of Apache Spark with YARN, Hadoop users can now use one Hadoop cluster with a single repository of data for a variety of purposes rather than having to segment workloads such that some data is dedicated to Apache Spark. More specifically, Hadoop users can now rest assured that YARN-based applications work collaboratively with applications that leverage Spark’s capabilities to facilitate real-time analytics, interactive analytics, machine learning and stream processing. Hortonworks introduced Apache Spark to the Hortonworks Data Platform as a technology preview download in May but today announces the integration of Spark with YARN, its recent acquisition, XA Secure, for authentication and data security purposes, as well as Ambari toward the larger goal of delivering an integrated, turnkey, enterprise-grade Hadoop platform. Thursday’s announcement by Hortonworks responds to similar statements by competitors MapR regarding the integration of Spark into its Hadoop distribution, and Cloudera’s announcement of its enterprise-grade support for Apache Spark.

The following graphic illustrating the integration of Spark into YARN originated from the Hortonworks blog post Making Apache Spark YARN Ready.

Categories: Hadoop, Hortonworks | Tags: , , , ,

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