Time series as a native data type in Redis

RedisTimeSeries simplifies the use of Redis for time-series use cases like IoT, stock prices, and telemetry.

With RedisTimeSeries, ingest and query millions of metrics and events per second using an optimal data structure. Advanced techniques such as downsampling and aggregation ensure a small memory footprint without impacting performance. Use a variety of queries for visualization and monitoring with built-in connectors to popular tools like Grafana, Prometheus, and Telegraf.

Introducing RedisTimeSeries at Redisconf19


The fastest time-series database

Get unmatched performance of time-series data processing, based on the industry-standard benchmark.

Purpose-built data structure

New data structure bundled with a set of commands for efficiently processing and querying time-series data.

Tight integrations with popular tools

Rapidly integrate with tools like Grafana, Prometheus, and Telegraf for monitoring, visualization, and data migration.

Use Cases

Data ingest

Ingest and process millions of time-stamped data per second with minimal latency using minimum resources.


Collect telemetry data from multiple remote devices on-premises, in any cloud, or on the edge for insights into IoT devices.


Gain deep insights into infrastructure and application health with integrations into Prometheus, Grafana, and Telegraf.

RediTimeSeries Sizing Calculator

Size your RediTimeSeries deployment according to your specific requirements.

Open Calculator

Try RedisTimeSeries

Community Edition
Enterprise Edition
   Redis Enterprise Cloud
   Redis Enterprise Software
   Latest Module Version

Main capabilities

Downsampling and retention

Automatically executes downsampling and retention rules with double-delta compression (available soon) to store large time-series datasets in a space-efficient manner.

Aggregation, range queries, and special counter operations

Powered by labeling and search techniques, implement multiple range queries and aggregations across several time series objects for real-time analysis. Use counter operations such as increment and decrement on the last value for telemetry applications.

Fast data ingest with infinite scale

Support millions of ingest operations/sec at sub-millisecond latency. Scale effortlessly by spanning a single time-series object across multiple Redis shards and nodes.

Visualization with Grafana, RedisInsight, and Telegraf

RedisTimeSeries is integrated with popular data collection, analytics, and monitoring libraries, including Telegraf for data ingest, Grafana for analytics and monitoring dashboards with the Prometheus adaptor, and RedisInsight to inspect your data in Redis.

Learn More