NoSQL from a RDBMS company

Oracle has announced an open source product for the NoSQL space, the Oracle NoSQL Database . Unlike other popular products including Redis, MongoDB, Cassandra, Voldermort and many others, Oracle has set a benchmark on the features that are truly necessary for highly available data systems.

Many products in the NoSQL space have told you that consistency is not needed, eventual consistency is good enough, that transactions are not performant enough to include as a feature. No standards exists, there is no common interface for communication, or key features that products aim to meet or better. With this product, features including transactions, replicated data and failover which are built in, are features other open source NoSQL products will need to match.

Oracle NoSQL Database is a key value store, supporting a major/minor key for co-locating regularly accessed information for more consistent data retrieval. The API (built in Java) supports GET, PUT, and DEL operators. The system is designed to not have a single point of failure, and to support a node failure without impact. The replication factor is reported to enable up to 7 copies of information, which would be a feature to support cross data center management. The database driver is latency aware, so this can support load balancing operations for optimal performance.

I am excited to hear about this and looking forward to evaluating the software. I will be watching more closely how the integration of MySQL and Oracle NoSQL can be an offering for startups and Web 2.0

Tagged with: Databases MySQL Oracle NoSQL Database

Related Posts

My take on PyCon Australia 2026

PyCon AU 2026 held in Brisbane this week was a five day event for the Python community. With specialized tracks and dedicated tutorial and engineering days there was a wide variety of content available.

Read more

Fixing Old Software Bugs Without Thinking

I previously came across an issue in my benchmarking work where I relied on the Latency Histogram section of sysbench output. On Linux it worked fine — I generally ran my workload there, so it never mattered.

Read more

Curating DuckDB Datasets Leveraging AI

In Curated MySQL Data Sets for Realistic Testing I described datasets assembled the manual way — download, schema, load, validate, document — over hours or days per source. This post is the follow-up I promised: what changes when AI assists the same workflow, using DuckDB as the target engine and GeoNames as the first example.

Read more