Apache HBase 1.3 Ships with Multiple Performance Improvements

by Alexandre Rodrigues on  Jan 30, 2017

Apache HBase 1.3.0 was released mid-January 2017 and ships with support for date-based tiered compaction and improvements in multiple areas, like write-ahead log (WAL), and a new RPC scheduler, among others. The release includes almost 1,700 resolved issues in total.

Julien Le Dem on the Future of Column-Oriented Data Processing with Apache Arrow

by Alexandre Rodrigues on  Dec 08, 2016 1

Julien Le Dem, the PMC chair of the Apache Arrow project, presented on Data Eng Conf NY on the future of column-oriented data processing. Apache Arrow is an open-source standard for columnar in-memory execution. InfoQ interviewed Le Dem to find out the differences between Arrow and Parquet.

Combine SQL Server with Hadoop Using PolyBase

by Jonathan Allen on  Jun 02, 2016 2

With the recently released SQL Server 2016, you can now use SQL queries against Hadoop and Azure blob storage. Not only do you no longer need to write map/reduce operations, you can also join relational and non-relational data with a single query.

Elephant in the Cloud - Hadoop as a Service

by Srini Penchikala on  May 02, 2016 2

Hadoop and other big data technologies revolutionized the way organizations run data analytics but the organizations are still facing challenges with operating costs of using these technologies for on-premise data processing. Ashish Thusoo recently spoke at Enterprise Data World Conference about Hadoop as a service offering that helps organizations bridge the gaps with these capabilities.

Google Cloud Machine Learning and Tensor Flow Alpha Release

by Dylan Raithel on  Apr 18, 2016

Late last month Google released an alpha version of their TensorFlow (TF) integrated cloud machine learning service as a response to a growing need to make their Tensor Flow library to run at scale on the Google Cloud Platform (GCP). Google describes several new feature sets around making TF usage scale by integrating several pieces of the GCP like Dataproc, a managed Hadoop and Spark service.

Apache Flink 1.0.0 is Released

by Rags Srinivas on  Mar 24, 2016

InfoQ's Rags Srinivas caught up with Stephan Ewen, a project committer for Apache Flink about the 1.0.0 Release and the roadmap

Hunk/Hadoop: Performance Best Practices

by Jonathan Allen on  Sep 23, 2015

When working with Hadoop, with or without Hunk, there are a number of ways you can accidentally kill performance. While some of the fixes require more hardware, sometimes the problems can be solved simply by changing the way you name your files.

Using Hunk+Hadoop as a Backend for Splunk

by Jonathan Allen on  Sep 22, 2015

Splunk can now store archived indexes on Hadoop. At the cost of performance, this offers a 75% reduction in storage costs without losing the ability to search the data. And with the new adapters, Hadoop tools such as Hive and Pig can process the Splunk-formatted data.

Splunk .conf 2015 Keynote

by Jonathan Allen on  Sep 22, 2015

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

by Jérôme Serrano on  Jun 11, 2015

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

by Srini Penchikala on  May 30, 2015

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.

Glenn Tamkin on Applying Apache Hadoop to NASA's Big Climate Data

by Srini Penchikala on  May 06, 2015

NASA Center for Climate Simulation (NCCS) is using Apache Hadoop for high-performance data analytics. Glenn Tamkin from NASA team, recently spoke at ApacheCon Conference and shared the details of the platform they built for climate data analysis with Hadoop.

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

by Srini Penchikala on  Apr 24, 2015

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

by Benjamin Darfler on  Apr 07, 2015

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

by Matt Raible on  Mar 05, 2015

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.