Basho Technologies releases Riak TS distributed NoSQL database to store and analyze time series data. Basho team recently announced at AWS re:invent event, the availability of Riak TS which is optimized for reads and writes of time series data generated from IoT devices, financial and economic data, and scientific observations.
Based on a masterless architecture in which every node in the cluster is capable of serving read and write requests, the distributed database automatically co-locates, replicates, and distributes data across the cluster to achieve performance and high availability. It also provides optimized range queries for data access requirements.
Riak TS is the third member of Basho’s storage instance model and complements the other two databases, Riak KV (used for storing Key Value unstructured data) and Riak S2 (optimized for storing distributed large objects such as videos, images and other files).
Riak TS database features include the following:
- Add nodes to the cluster without sharding; data is automatically and uniformly distributed across the cluster.
- Data co-location ensures that time series data is located on the same node based on time, geohash or both to prevent hot spots in clusters. Composite keys (based on time, geohash or data family) can be used to define sort order on disk for read performance.
- Data Definition Language (DDL) for table and field definitions supports both structured and semi-structured data. Since time series data can be typed, developers can define their own schema.
- Ensure data accuracy with the ability to validate data on input.
- Query data with SQL-like queries.
- Application integration with APIs and client libraries in different languages like Java, Ruby, Python, Go, Erlang, Node.js and .NET.
- Integration with Apache Spark Big Data processing framework using the Apache Spark add-on for operational analysis of time series data.
Riak TS is integrated with Basho Data Platform (BDP), which includes support for Apache Spark, Redis for data caching via Redis add-on, and Apache Solr add-on for distributed search queries.
If you are interested in learning more about Riak TS or other Riak technologies, checkout their community and documentation websites.