UPDATED 23:23 EDT / NOVEMBER 18 2015

NEWS

Splice Machine revs up RDBMS solution with Apache Spark

Splice Machine Inc. has added some analytical muscle to its SQL-RDBMS-on-Hadoop solution by tapping into Apache Spark’s in-memory technology. The result is a hybrid SQL database businesses can use to perform transactional and analytical workloads in tandem.

The database is already a popular alternative to handling multi-terabyte workloads on conventional relational databases like Oracle’s, running at an order of magnitude faster and at a substantially lower cost thanks to Hadoop’s native scale-out architecture.

Splice Machine version 2.0, which is now available in beta, builds on this by integrating two separate processing engines – HBase and now Spark – and dividing incoming workloads between them depending on whether they’re OLTP or OLAP. This means that OLTP and OLAP workloads can run side-by-side while using the same architecture and data, without any performance sacrifice.

“The Splice Machine RDBMS is an innovative hybrid of in-memory technology from Spark and disk-based technology from Hadoop,” the company said in a statement. “Unlike in-memory-only databases, the Splice Machine RDBMS does not force companies to put all of their data in-memory, which can become prohibitively expensive as data volume grows. It uses in-memory computation to materialize the intermediate results of long-running queries but uses the power of HBase to durably store and access data at scale.”

In Splice Machine 2.0, HBase handles the traditional queries while Spark processes the OLAP queries. This division of workloads means that the database can segregate CPU and memory usage for each kind of query. In turn, this ensures that larger, complex analytical processing queries do not impact on time-sensitive transactional ones, the company says. Indeed, users even have the ability to setup priority levels for different analytical queries so they can ensure the most important jobs are not held up by massive batch processes that consume heavy resources.

The net gain is a performance boost of between ten and twenty times that of traditional relational database management systems, and it comes at just a quarter of the cost, Splice Machine claimed.

As tantalizing as it sounds, Splice Machine’s database is just one option in a swarm of solutions that’s growing by the minute. The database arena is being flooded with all manner of NoSQL and NewSQL solutions aimed at solving specific use cases at extremely high speeds, while legacy database vendors such as Oracle and Microsoft are pushing their own in-memory and NoSQL offerings to with numerous upstarts nipping at their heels. Startups like Splice Machine therefore need to carve out a specific niche for themselves, and the company says Splice Machine 2.0 is especially well-suited for digital marketing, data warehouse, operational data lakes and Internet of Things’ workloads.

Image credit: Unsplash via pixabay.com

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