Spark-powered Splice Machine goes open source

An open source version of the Hadoop-based and Spark-accelerated RDBMS is now available sans a few enterprise features

Spark-powered Splice Machine goes open source

Splice Machine, the relational SQL database system that uses Hadoop and Spark to provide high-speed results, is now available in an open source edition.

Version 2.0 of Splice Machine added Spark to speed up OLAP-style workloads while still processing conventional OLTP workloads with HBase. The open source version, distributed under the Apache 2.0 license, supplies both engines and most of Splice Machine's other features, including Apache Kafka streaming support. However, it omits a few enterprise-level options like encryption, Kerberos support, column-level access control, and backup/restore functionality.

Splice Machine is going open source for two reasons. First, to get into the hands of developers, letting them migrate data to it, test it on their own hardware or in the cloud, then upgrade to the full version if it fits the bill. Motive No. 2, as is the case with any open source project, is to allow those developers to contribute back to the project if they're inclined.

The first motive is more relevant here. Originally, Splice Machine was offered in a free-to-use edition minus some enterprise features. The open source version provides a less ambiguous way to offer a freebie, as there's less fear a user will casually violate the license agreement by enabling the wrong item (see: Oracle). Going open source also helps defray criticisms about Splice Machine as a proprietary black box, which InfoWorld's Andy Oliver hinted at in his original 2014 discussion of the database.

Splice Machine CEO Monte Zweben stated in an email that "[e]nterprises are now increasingly committed to open source technologies because they are less locked in to individual companies and able to tap a wider community of resources dedicated to the technology. We have learned that the first steps towards building community are to remove friction and to be transparent."

Aside from downloading the bits and deploying them locally, users can try out Splice Machine via a "sandbox" -- a cloud-hosted instance that runs on AWS and allows a developer to spin up a Splice Machine cluster for testing.

Despite employing Hadoop and Spark under the hood, Splice Machine's main selling points are about its scale-out functionality, with Hadoop and Spark as convenient bonuses for those who want to use them directly. The introduction of the open source version doesn't change that emphasis, although it remove any licensing or usage ambiguities that a company might face if it wants to deploy Splice Machine on a trial basis.

Going open source doesn't guarantee increase uptake, though, since the biggest obstacle faced by Splice Machine has typically been getting a foothold in a market where incumbent solutions are hard to break away from. That said, Splice Machine offers consultancy services to aid migrations, although only in conjunction with the enterprise product.

[This article was edited to add comment from Splice Machine CEO.]

Copyright © 2016 IDG Communications, Inc.

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