With the 1.0 release of Apache Drill and a new 1.2 release of Apache Hive, everything you thought you knew about SQL-on-Hadoop might just have become obsolete
Big on Data
Veteran data geek Andrew Brust covers Big Data technologies including Hadoop, NoSQL, Data Warehousing, BI and Predictive Analytics.
Andrew Brust has worked in the software industry for 25 years as a developer, consultant, entrepreneur and CTO, specializing in application development, databases and business intelligence technology. He has been a developer magazine columnist and conference speaker since the mid-90s, and a technology book writer and blogger since 2005. Andrew serves as Senior Director, Technical Product Marketing and Evangelism at Datameer, a big data analytics company.
Hadoop is here to stay. But it's mature analytics tools for Hadoop, DBMS abstraction layers over it and Hadoop-as-a-Service cloud offerings that will make the open source Big Data platform actionable.
New Azure Data Warehouse offering finally offers competition to Amazon Redshift. Azure Data Lake and new scaling models for Azure SQL Database round out the offerings.
Major RDBMSes support RLS natively; Google has announced its BigQuery service does too.
In 2010, Google launched its Prediction API. The month before last, Microsoft's Azure Machine Learning service went into general availability. Last week, Amazon announced its own machine learning offering and Microsoft closed its acquisition of Revolution Analytics.
Belief in the quality of a platform tends to self-fulfill. Will that be the case with Apache Spark? Vendors seem so far ahead of customers on Spark that it's almost worrisome.
Some closing thoughts about Big Data, in my last post as ZDNet's Big on Data guy.
Hortonworks' leading Hadoop distro now includes Stinger, Solr, Storm, security and governance, on Windows and Linux.
Pivotal reveals its strategy for unifying different data technologies: License them all together.
SAP's promise to bring all its products onto HANA gains credibility today as Business Warehouse 7.4 signs on.
Cloudera has raised a bunch of money. Again. In this guest post, Tony Baer explains what the new investment means for Cloudera, Hadoop and the data warehousing space.
The next release of Redmond's flagship relational database is done. In-memory computing; cloud and hybrid scenarios; and enhanced data warehousing capabilities are the product's major new features.
The darling of data discovery and the master of machine data offer tight integration.
The Hadoop-based in-memory cluster computing engine moves from Apache incubator status to top-level project
And so the consolidation begins. Megavendor IBM agrees to acquire prominent NoSQL player Cloudant.