Basho open sources Riak TS

Database optimised for Internet of Things applications.

  • 8 years ago Posted in
Basho Technologies has introduced the latest release of Basho Riak TS, version 1.3. Riak TS is the only enterprise-grade NoSQL database optimized for Internet of Things (IoT). The open source version enables developers to download the software for free and use it in production as well as make contributions to the code and develop applications around Riak TS. Enhancements to Riak TS make it quick, easy and cost-effective to spin up an instance to test new ideas and build IoT applications. In addition to making Riak TS available as open source software, version 1.3 expands support for SQL commands, enhances API support and provides support for shell commands. Riak TS Enterprise 1.3 also includes Multi-Cluster Replication.

 

Basho believes strongly in supporting the global distributed systems developer community, which spends their valuable time maintaining open source software to solve critical distributed infrastructure problems facing the industry. The Basho community at large also contributes projects directly to the Basho Labs Repository, a 100-percent community-driven repository to share code freely and regularly.

 

Growth of IoT Use Case Increases Demand for Flexible, Purpose-Built Database

"In a recent ESG survey, 48 percent of respondents declared big data and analytics initiatives their number one priority; an additional 32 percent rank big data and analytics initiatives in their top five priorities," said Nik Rouda, senior analyst, ESG. "Today, big data is maturing into a pervasive IT undertaking that requires active collaboration from all of an organization's various operating facets. A very common goal is implementing tools built for operational efficiency. Especially as data variety grows — in the form of unstructured, often time-stamped IoT data — deriving value from data more quickly and at lower costs will be paramount for competitive advantage. Riak TS 1.3 represents a robust purpose-built solution for time series data making big data analytics projects easier to deploy, manage and maintain.”

 

Increasingly, IoT is generating time series data — data marked with a timestamp — from a variety of sources, such as sensors. The sheer volume of time series data these sources generates requires databases that can efficiently and reliably store and query time series data. Riak TS delivers on this need and allows both open source and commercial customers to perform the associated queries and transactions on time series data, while maintaining high availability and scale.

 

“The data-rich experiences Intellicore provides to all screens, be they handheld or broadcast, that deliver on the promises made by our global customers, such as Formula E, require real-time processing and analysis of large streams of sensor information with literally hundreds of models running to provide the enhanced user experience viewers demand,” said Christian Trotobas, founder and CEO, Intellicore. “Uncovering and leveraging insight and value in real time from many different data streams is very challenging, and we quickly reached the limits of existing database technologies. Because Basho’s Riak TS is engineered and optimized for time series data sets, Intellicore’s ability to rapidly deliver at massive scale has been enhanced.”

 

Riak TS 1.3 Offers High Availability, Massive Scalability and Cost-Effective Operations

Riak TS is built on Riak Core, a distributed systems framework known for its resilience, fault tolerance and horizontal scalability, that uses commodity hardware and simplicity of operational management. Its masterless architecture is designed for operational simplicity and high availability, even in the event of hardware failures or network partitions. As well as now being available as open source software, Riak TS enables:

?        Fast storage and retrieval of time series data: As an enterprise time series database, Riak TS co-locates data together in the same physical part of the cluster based on time range. This enables faster queries so that your time series data is faster to read and analyze. 

?        Easy analysis of large data sets: Riak TS 1.3 enables enhanced SQL commands and range queries for unstructured and structured data so business analysts can more easily analyze data.

?        Integration with complimentary stack technologies: Riak TS also seamlessly integrates with Apache Spark. The Spark connector efficiently retrieves data from Riak TS to Spark for in-memory distributed processing so the results can be stored back in Riak TS as needed. The ability to persist these results to Riak TS provides flexibility for future data processing or analysis. Riak TS also offers support for Spark Streaming, DataFrames and Spark SQL.

?        Global availability: Riak TS Enterprise offers Multi-cluster Replication so that data stored in Riak TS can be replicated for backup clusters, analysis clusters, or for multiple datacenters. With Riak TS Enterprise, data can be replicated across the datacenter or across geographic areas, providing disaster recovery, data locality, compliance with regulatory requirements, the ability to “burst” peak loads into public cloud infrastructure and more.

?        Enhanced support: The newest release also enhances support for APIs and SQL shell commands.

?        Simplified development and deployment: AWS Amazon Machine Images (AMI) will be available for Riak TS, so enterprises  can easily spin up Riak TS on AWS Workplace.

 

“Riak TS is the first enterprise database built specifically for time series data,” said Adam Wray, CEO, Basho Technologies. “As enterprises collect IoT time series data from sensors, they will need fast, reliable and scalable read and write performance. Riak TS is purpose-built to store and retrieve time series data with enhanced read and write performance. Extending an open-source version, enhancing ease of use, and adding support for Multi-cluster Replication will make it even easier for companies and community to demonstrate return on their IoT investments.”
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