Traditional databases were designed for transactional use cases, with a rigid labeling structure that cannot accommodate unstructured data. Time series data, on the other hand, is broadly defined as a series of data stored in time order, such as stock prices over many years, or CPU performance metrics from the past few hours.
Time series data is widely used across many industry verticals, and has carved out its own category among databases as relational, document-oriented and streaming databases do not fulfill the needs of this particular type of data.
RedisTimeSeries guarantees fast data ingest, resource efficiency, easy and fast queries, ready integrations, and client libraries in a number of popular languages. It can also act as an intermediary between your application and any database not designed specifically for time series use cases.
RedisTimeSeries combines all the benefits of Redis and a purpose-built time series database. It can help your business in many ways, including by saving on resources, supporting more end users and bringing your apps to market faster with easy integration.
Download the RedisTimeSeries white paper to learn::
You will also receive a link to this document at the email address you provided. Browse additional resources from our library of Case Studies, Benchmarks, and more!
By continuing to use this site, you consent to our updated privacy agreement. You can change your cookie settings at any time but parts of our site will not function correctly without them.