Basho Riak® TS <http://www.basho.com/riak-ts>, a distributed NoSQL database architected to aggregate and analyze massive amounts of sequenced, unstructured time series data, is now available as an Open Source database. See the blog <http://basho.com/posts/business/riak-ts-1-3-is-now-open-source-what-is-here-and-what-is-coming/> by our CTO, Dave McCrory to learn more about where it is now and what is to come.
Riak TS is optimized to deliver reliable, scalable and fast reads and writes so thatorganizations can effectively meet their application time series data storage and retrieval needs. And like Riak KV <http://basho.com/products/riak-kv/>, Riak TS provides high availability and massive scalability. Riak TS can be operationalized at lower costs than traditional relational databases and is easy to manage at scale. Unlike other NoSQL databases, Riak TS enables customers to take advantage of time series applications with the ability to: - Ensure IoT or time series applications are always available for both read and write operations, with the ability to easily scale as devices or users increase. - Add nodes to the cluster without sharding. With Riak TS, data is automatically and uniformly distributed across the cluster. - Achieve faster read and write performance and predictably, even under peak loads. Data co-location ensures that time series data is located on the same node to prevent hot spots in clusters. Internal testing shows Riak TS to be faster than Cassandra at both writes and queries. - Ensure data accuracy with the ability to validate data on input. - Leverage SQL queries programmatically or via a SQL shell to create tables, describe tables and select data from the tables - Analyze data using aggregators and arithmetic operations - Meet unique application needs with robust HTTP APIs and client libraries including code in Java, Ruby, Python, Go, Erlang, Node.js or .NET. - Seamlessly integrate with Apache Spark to ensure easier and faster operational analysis of time series data. - Replicate clusters across the datacenter or across the globe for data geo-location, secondary analytics clusters or disaster recovery. - AWS Amazon Machine Images (AMI) will be available for Riak TS, so enterprises can easily spin up Riak TS on AWS Workplace. Technical details: 1. Create tables using the CREATE TABLE statement. Table schema can be discovered using a DESCRIBE TABLE statement. 2. Insert data using the INSERT statement. 3. Query data from the table using the SELECT statement. Filtering on primary and non-primary keys is supported 4. Aggregations – You can apply a function like count, sum, avg, min, max or stddev to your SQL SELECT statement WHERE clause. 5. Arithmetic operations – operations like +, -, /, * and () can be used in a SQL SELECT /WHERE 6. Leverage client libraries including code in Java, Ruby, Python, Go, Erlang, Node.js or .NET. 7. Integrate with Spark using Spark connector Supporting resources: - Riak® TS <http://basho.com/products/riak-ts/> - Documentation <http://docs.basho.com> - Basho Blog <http://basho.com/blog/> - Downloads <http://docs.basho.com/riak/ts/1.3.0/downloads/> - Link to Source <https://github.com/basho/riak/releases/tag/riak_ts-1.3.0> Let us know what you think! Regards Seema Jethani
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