According to Accenture, the IoT will add $14.2 trillion to the global economy by 2030, enabling companies to capture new growth and boost revenue. As more and more enterprise applications collect IoT data, specifically time series data from sensors, they need fast, reliable and scalable read and write performance. To best accomplish this, the data must be stored, queried and analysed together. Unlike traditional databases, Riak TS is built to store and retrieve time series data with enhanced read and write performance.
Like Riak KV, Riak TS provides high availability and massive scalability. Riak TS can be operationalised 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 based on time, geohash or both to prevent hot spots in clusters.
- Ensure data accuracy with the ability to validate data on input.
- Query data with SQL-like queries.
- Meet unique application needs with robust 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.
Integrate with the Basho Data Platform, which supports multiple database models, taking the complexity out of building and deploying active workloads in Big Data, IoT and hybrid cloud applications.
