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.
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.
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.