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Splice Machine Targets Oracle, MySQL with Hadoop Relational Database

Splice Machine updated what it claims to be the first "Hadoop RDBMS," targeting enterprises using Oracle and MySQL relational database management systems.

After announcing a beta release in May of last year, the San Francisco startup went on to make waves the Big Data world with its singular approach before launching version 1.0 last November.

Now, with today's update, "We've added multiple enterprise-ready features that enable businesses to confidently replace their traditional RDBMSs, such as Oracle & MySQL, with an affordable, scale-out alternative that delivers 5-10x greater performance at one fourth the cost," the company said.

As outlined by Splice machine, those new features include improved SQL compliance, BI tool compatibility, incremental backup, improved performance and other enhancements.

"We are particularly proud of the improvements to our cost-based optimizer, which dramatically improves performance on analytical queries," the company said. "In 1.5, we have combined industry standards like SQL and ACID compliance with a modern scale-out architecture -- giving businesses the ability to power real-time applications and analytics in a single database platform."

How Splice Machine technology works with other components.
[Click on image for larger view.] How Splice Machine Works with Other Components.
(source: Splice Machine)

Built on top of the open source Java-based Apache Derby relational database and Hbase -- an open source, distributed non-relational database, working with Hadoop -- the Splice Machine database is ACID-compliant and is used to power online analytical processing (OLAP) and online transaction processing (OLTP) workloads, according to the company.

"Unlike many other so-called SQL-on-Hadoop projects, Splice Machine delivers actual enterprise-grade SQL on Hadoop, enabling support of operational applications and analytics, as well as ETL acceleration," Splice Machine quoted Dan Woods at CITO Research as saying. "ETL acceleration is often the first project on Hadoop for many companies. Splice Machine's transactional capabilities ensure that Hadoop gracefully handles ETL errors and data quality issues without reloading all of the data. Furthermore, Splice Machine can enable incremental ETL that can drive down ETL lag from days to seconds."

With varied per-node pricing plans, the updated database is now available for download and evaluation.

About the Author

David Ramel is the editor of Visual Studio Magazine.

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