Optimized to Handle Time Series Data, Riak TS is the Database of Choice for the Internet of Things
LAS VEGAS – AWS re:Invent – Oct. 6, 2015 – Riak Technologies, the creator and developer of Riak® software, today announced Riak Riak® TS, a distributed NoSQL database architected to aggregate and analyze massive amounts of sequenced, unstructured data generated from the Internet of Things (IoT) and other time series data sources. Riak TS is optimized to deliver reliable and scalable reads and writes at unmatched speeds, so organizations can effectively meet their application time series data storage and retrieval needs.
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 analyzed 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 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 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 Riak 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.
Quotes
- “At The Weather Company, we manage 20 terabytes of new data a day, including real-time forecasting data from over 130,000 sources. The sheer volume of time series data requires databases that can efficiently and reliably store and query time series data. Riak TS delivers on this need and allows us to perform the associated queries and transactions on time series data, while maintaining high availability and scale.” – Bryson Koehler, executive vice president and CIO, The Weather Company
- “In today’s Internet of Everything, people, processes, data and things are all connected and generating tremendous amounts of data. Sensors in particular generate mountains of time series data that is often stored at the network edges and gathered in the cloud. The integration of NoSQL and Spark will play a vital role in analyzing this data to identify patterns and generate insights, and the introduction of Riak TS makes analyzing this data simple, effective and scalable.” – Ken Owens, chief technology officer for Cisco Intercloud Services
- “It’s clear the only way to scale for the Internet of Things is with very distributed applications and data stores. We manage data from millions of smart meter endpoints supporting hundreds of utilities and look to distributed systems leaders like Riak for optimized solutions for high volume time series data.” – Paul Barry, director, Temetra
- “The rise of unstructured data presents a significant opportunity for innovation. As a result, companies are demanding database solutions that are operationally easy and specifically optimized to handle this type of data. Built on the same core Riak foundation, we now provide a solution specifically optimized for storing and retrieving unstructured data, making us the only NoSQL player that has specialized offerings for key value, large object and time series data. With Riak TS, customers can more easily scale and execute on Internet-of-Thing uses cases and more.” – Adam Wray, CEO, Riak
Riak will demonstrate Riak TS at AWS re:Invent, which takes place October 6-9, 2015 in Las Vegas. To learn more, stop by the Riak booth #829 or visit riak.com/products/riak-ts.
Supporting Resources
- Riak Blog – The Data Platform
- Riak Website
- Riak Blog
- Riak® KV (formerly Riak) software
- Riak® S2 (formerly Riak CS) software
- Additional Resources
- Twitter: @Riak
About Riak Technologies
Riak Technologies, Inc. is a distributed systems company dedicated to developing disruptive technologies that simplify enterprises’ most critical data management challenges. Riak has attracted one of the most talented groups of engineers and technical experts ever assembled devoted exclusively to solving some of the most complex issues presented by scaling distributed systems and enjoys a large and growing following among influential programmers, architects and academics.
Riak’s distributed database, Riak KV, the industry leading distributed NoSQL database, and Riak’s cloud storage software, Riak S2, are used by fast-growing Web businesses and by one-third of the
Fortune 50 to power their critical Web, mobile and social applications, and their public and private cloud platforms. The Riak Data Platform was recently introduced to help enterprises control and simplify distributed Big Data. Riak is the organizer of RICON – a distributed systems conference.
Riak is the registered trademark of Riak Technologies, Inc. The trademarks and names of other companies and products mentioned herein are the property of their respective owners.
Press Contact
Michael Kellner
BOCA Communications for Riak
basho@bocacommunications.com
415-425-4773
