InfoQ Homepage Hadoop Content on InfoQ
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Cloudera and Hortonworks Merge with Goal to Increase Competition with Cloud Offerings
Earlier this month, Cloudera and Hortonworks announced an all-stock merger at a combined value of around $5.2 billion. Analysts have argued that this merger is aimed at increased competition that both companies are facing from cloud vendors like Amazon, Google and Microsoft. In this article we log reactions from analysts and the industry, and the implications for current customers.
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Dataiku's Latest Release Integrates Deep-Learning for Computer Vision
Collaborative data science platform Dataiku's latest release of its Data Science Studio includes pre-trained deep learning models for image processing. The DSS platform implements each step of a data-science project from data-sourcing and visualization to production deployment. Its machine-learning module supports standard libraries and it integrates with Hadoop and multiple Spark engines.
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DevOps Workbench Launched by ZeroStack
Private cloud provider, ZeroStack, has announced a self-service capability from which developers can create their own workbenches. Forty developer tools from a mix of open source and commercial providers are available to users of the DevOps Workbench through Zerostack’s Intelligent Cloud Platform.
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Julien Le Dem on the Future of Column-Oriented Data Processing with Apache Arrow
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.
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Combine SQL Server with Hadoop Using PolyBase
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.
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Elephant in the Cloud - Hadoop as a Service
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.
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Google Cloud Machine Learning and Tensor Flow Alpha Release
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.
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Apache Flink 1.0.0 is Released
InfoQ's Rags Srinivas caught up with Stephan Ewen, a project committer for Apache Flink about the 1.0.0 Release and the roadmap
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Hunk/Hadoop: Performance Best Practices
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.
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Using Hunk+Hadoop as a Backend for Splunk
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.
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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.
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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.
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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.
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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.
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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.