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  • Splunk .conf 2015 Keynote

    Splunk opened their big data conference with an emphasis on “making machine data accessible, usable, and valuable to everyone”. This is a shift from their original focus: indexing arbitrary big data sources. Reasonably happy with their ability to process data, they want to ensure that developers, IT staff, and normal people have a way to actually use all of the data their company is collecting.

  • Parquet Becomes Top-Level Apache Project

    Apache Parquet, the open-source columnar storage format for Hadoop, recently graduated from the Apache Software Foundation Incubator and became a top-level project. Initially created by Cloudera and Twitter in 2012 to speed up analytical processing, Parquet is now openly available for Apache Spark, Apache Hive, Apache Pig, Impala, native MapReduce, and other key components of the Hadoop ecosystem.

  • MemSQL 4 Database Supports Community Edition, Geospatial Intelligence and Spark Integration

    Latest version of MemSQL, in-memory database with support for transactions and analytics, includes a new Community Edition for free use by organizations. MemSQL 4, released last week, also supports integration with Apache Spark, Hadoop Distributed File System (HDFS), and Amazon S3.

  • Hortonworks, IBM and Pivotal to Support Open Data Platform in Their Big Data Solutions

    Big data vendors Hortonworks, IBM, and Pivotal recently announced that their Hadoop based platform products will use the common Open Data Platform (ODP). They made the announcement at the recent HadoopSummit Europe Conference of the open platform which includes Apache Hadoop 2.6 (HDFS, YARN, and MapReduce) and Apache Ambari software.

  • Apache HBase Hits 1.0

    After three developer previews, six release candidates and over 1500 closed tickets the Apache foundation has announced version 1.0 of Apache HBase, a NoSQL database in the Hadoop ecosystem. After more than 7 years of active development, the team behind HBase felt that the project had matured and stabilized enough to warrant a 1.0 version.

  • Spring XD 1.1: Simplifying Big Data like Spring Did for Java EE

    Pivotal recently released Spring XD 1.1 GA with new features including stream processing with Reactor, RxJava, Spark Streaming and Python. Additionally support for Kafka, batching and compression with RabbitMQ, and support for container group management when running on YARN are now featured.

  • Google Open Sources MapReduce Framework for C to Run Native Code in Hadoop

    Google announced last week the release of open source MapReduce framework for C, called MR4C, that allows developers to run native code in Hadoop framework. MR4C framework brings together the performance and flexibility of natively developed algorithms with the scalability and throughput provided by Hadoop execution framework.

  • Project Pachyderm Aims to Build a "Modern" Hadoop on Docker

    Project Pachyderm Aims to Build "Modern" Hadoop using Docker and CoreOS.

  • Apache Hive 1.0 Released, HiveServer2 Becomes Main Engine, Stable API Defined

    Apache Hive has released version 1.0 of their project on February 6th, 2015. Originally planned as version 0.14.1, the community voted to change the version numbering to 1.0.0 to reflect the amount of maturity the project has reached.

  • Splice Machine Version 1.0 Supports Integration with Hadoop and Analytic Window Functions

    Splice Machine version 1.0 supports analytic window functions and integration with Hadoop ecosystem. Splice Machine team recently released their Hadoop based RDBMS data management solution that can be used for transactional workloads on Hadoop.

  • LinkedIn Open Sources Cubert With an Eye To Big Data Analytics

    LinkedIn recently open sourced Cubert, its High Performance Computation Engine for Complex Big Data Analytics. Cubert is a framework written for analysts and data scientists in mind.Developed completely in Java and expressed as a scripting language, Cubert is designed for complex joins and aggregations that frequently arise in the reporting world.

  • Gobblin, LinkedIn's Unified Data Ingestion Platform

    At the 2014 QCon San Francisco conference, LinkedIn's Lin Qiao gave a talk on their Gobblin project (also summarized in a blog post) that is a unified data ingestion system for their internal and external data sources.

  • Stripe Open Sources Tools For Apache Hadoop

    Stripe, the internet payments infrastructure company recently announced open sourcing a set of internally developed tools based on Apache Hadoop.Timberlake, Brushfire, Sequins and Herringbone all contribute to enriching the available tools for building an Apache Hadoop stack.

  • Spark Sets New Record in Sort Performance

    Databricks has recently announced a new record in the Daytona GraySort contest using the Spark processing engine. The Daytona GraySort contest is a 3rd party benchmark measuring how fast a system can sort 100 Terabytes of data. Databricks posted a throughput of 4.27 TB/min over a cluster of 206 machines for their official run.

  • Hortonworks Data Platform Makes an Enterprise Push

    Hortonworks Data Platform (HDP) version 2.2 with features based around Hadoop and YARN has better support for enterprise features such as security, compliance and so on as well.

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