Riak TS Database
Riak TS is a distributed NoSQL database optimized for IoT and time series data.
#What is Riak TS?
Riak TS is a distributed NoSQL database developed by Basho Technologies. It is designed specifically for storing and analyzing time series data, which is data that changes over time and is identified by a timestamp. The database is open source and is built on top of the Riak core, which is a highly available and fault-tolerant distributed key-value store.
#Riak TS Key Features
Here are some of the most recognizable features of Riak TS database:
- Scalability: Riak TS is a highly scalable database that can handle large amounts of time series data.
- High availability: The database is designed to be highly available and fault-tolerant, with built-in replication and automatic failover capabilities.
- Querying: Riak TS provides an SQL-like query language called “Time Series Query Language” (TSQL) for querying time series data.
- Distributed architecture: Riak TS is built on top of a distributed key-value store, which enables it to distribute data across multiple nodes and handle large workloads.
- Multi-datacenter replication: Riak TS supports multi-datacenter replication, which allows for geographically distributed deployments and disaster recovery.
- Integration: Riak TS can be integrated with a variety of tools and technologies, including Apache Spark, Apache Kafka, and Elasticsearch.
#Riak TS Use-Cases
Here are some of the use-cases for Riak TS database:
- Internet of Things (IoT): Riak TS is well-suited for storing and analyzing data from IoT devices, which often produce time series data.
- Financial services: Riak TS can be used to store and analyze financial data, such as stock prices, market data, and trading data.
- Monitoring and logging: Riak TS can be used to store and analyze monitoring and logging data, such as server logs, network traffic data, and application metrics.
#Riak TS Summary
Riak TS is a distributed NoSQL database designed specifically for storing and analyzing time series data. It provides high scalability, availability, and fault-tolerance, as well as a SQL-like query language and integration with various tools and technologies. Its use-cases include IoT, financial services, and monitoring/logging.