RedisTimeSeries is a time-series database (TSDB) module for Redis, by Redis.
RedisTimeSeries can hold multiple time series. Each time series is accessible via a single Redis key (similar to any other Redis data structure).
A Redis time series comprises:
-
Raw samples: each raw sample is a {time tag, value} pair.
-
Time tags are measured in milliseconds since January 1st, 1970, at 00:00:00.
Time tags can be specified by the client or filled automatically by the server.
-
64-bit floating-point values.
The intervals between time tags can be constant or variable.
Raw samples can be reported in-order or out-of-order.
Duplication policy for samples with identical time tags can be set: block/first/last/min/max/sum.
-
-
An optional configurable retention period.
Raw samples older than the retention period (relative to the raw sample with the highest time tag) are discarded.
-
Series Metadata: a set of name-value pairs (e.g., room = 3; sensorType = ‘xyz’).
RedisTimeSeries supports cross-time-series commands. One can, for example, aggregate data over all sensors in the same room or all sensors of the same type.
-
Zero or more compactions.
Compactions are an economical way to retain historical data.
Each compaction is defined by:
- A timeframe. E.g., 10 minutes
- An aggregator: min, max, sum, avg, …
- An optional retention period. E.g., 10 year
For example, the following compaction: {10 minutes; avg; 10 years} will store the average of the raw values measured in each 10-minutes time frame - for 10 years.
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- Sensor data: e.g., temperatures or fan velocity for a server in a server farm
- Historical prices of a stock
- Number of vehicles passing through a given road (count per 1-minute timeframes)
- High volume inserts, low latency reads
- Query by start time and end-time
- Aggregated queries (Min, Max, Avg, Sum, Range, Count, First, Last, STD.P, STD.S, Var.P, Var.S, twa) for any time bucket
- Configurable maximum retention period
- Compactions - automatically updated aggregated timeseries
- Secondary index - each time series has labels (name-value pairs) which will allows to query by labels
In the RedisTimeSeries organization you can find projects that help you integrate RedisTimeSeries with other tools, including:
- Prometheus - read/write adapter to use RedisTimeSeries as backend db.
- Grafana - using the Redis Data Source.
- Telegraf
- StatsD, Graphite exports using graphite protocol.
RedisTimeSeries is part of Redis Stack.
You can either get RedisTimeSeries setup in a Docker container or on your own machine.
To quickly try out RedisTimeSeries, launch an instance using docker:
docker run -p 6379:6379 -it --rm redis/redis-stack-server:latest
You can also build RedisTimeSeries on your own machine. Major Linux distributions as well as macOS are supported.
First step is to have Redis installed, of course. The following, for example, builds Redis on a clean Ubuntu docker image (docker pull ubuntu
) or a clean Debian docker image (docker pull debian:stable
):
mkdir ~/Redis
cd ~/Redis
apt-get update -y && apt-get upgrade -y
apt-get install -y wget make pkg-config build-essential
wget https://download.redis.io/redis-stable.tar.gz
tar -xzvf redis-stable.tar.gz
cd redis-stable
make distclean
make
make install
Next, you should get the RedisTimeSeries repository from git and build it:
apt-get install -y git
cd ~/Redis
git clone --recursive https://github.com/RedisTimeSeries/RedisTimeSeries.git
cd RedisTimeSeries
# If you forgot to clone the repo with submodules, you can fix it by running the following command
# git submodule update --init --recursive
./sbin/setup
bash -l
make
Then exit
to exit bash.
Note: to get a specific version of RedisTimeSeries, e.g. 1.8.10, add -b v1.8.10
to the git clone
command above.
Next, run make run -n
and copy the full path of the RedisTimeSeries executable (e.g., /root/Redis/RedisTimeSeries/bin/linux-x64-release/redistimeseries.so
).
Next, add RedisTimeSeries module to redis.conf
, so Redis will load when started:
apt-get install -y vim
cd ~/Redis/redis-stable
vim redis.conf
Add: loadmodule /root/Redis/RedisTimeSeries/bin/linux-x64-release/redistimeseries.so
under the MODULES section (use the full path copied above).
Save and exit vim (ESC :wq ENTER)
For more information about modules, go to the Redis official documentation.
Run redis-server in the background and then redis-cli:
cd ~/Redis/redis-stable
redis-server redis.conf &
redis-cli
After you setup RedisTimeSeries, you can interact with it using redis-cli.
Here we'll create a time series representing sensor temperature measurements. After you create the time series, you can send temperature measurements. Then you can query the data for a time range on some aggregation rule.
$ redis-cli
127.0.0.1:6379> TS.CREATE temperature:3:11 RETENTION 60 LABELS sensor_id 2 area_id 32
OK
127.0.0.1:6379> TS.ADD temperature:3:11 1548149181 30
OK
127.0.0.1:6379> TS.ADD temperature:3:11 1548149191 42
OK
127.0.0.1:6379> TS.RANGE temperature:3:11 1548149180 1548149210 AGGREGATION avg 5
1) 1) (integer) 1548149180
2) "30"
2) 1) (integer) 1548149190
2) "42"
Some languages have client libraries that provide support for RedisTimeSeries commands:
Project | Language | License | Author | Stars | Package | Comment |
---|---|---|---|---|---|---|
jedis | Java | MIT | Redis | Maven | ||
redis-py | Python | MIT | Redis | pypi | ||
node-redis | Node.js | MIT | Redis | npm | ||
nredisstack | .NET | MIT | Redis | nuget | ||
redistimeseries-go | Go | Apache-2 | Redis | GitHub | ||
rueidis | Go | Apache-2 | Rueian | GitHub | ||
phpRedisTimeSeries | PHP | MIT | Alessandro Balasco | GitHub | ||
redis-time-series | JavaScript | MIT | Rafa Campoy | GitHub | ||
redistimeseries-js | JavaScript | MIT | Milos Nikolovski | GitHub | ||
redis_ts | Rust | BSD-3 | Thomas Profelt | GitHub | ||
redistimeseries | Ruby | MIT | Eaden McKee | GitHub | ||
redis-time-series | Ruby | MIT | Matt Duszynski | GitHub |
The module includes a basic set of unit tests and integration tests.
Unit tests
To run all unit tests, follow these steps:
$ make unit_tests
Integration tests
Integration tests are based on RLTest, and specific setup parameters can be provided to configure tests. By default the tests will be ran for all common commands, and with variation of persistency and replication.
To run all integration tests in a Python virtualenv, follow these steps:
$ mkdir -p .env
$ virtualenv .env
$ source .env/bin/activate
$ pip install -r tests/flow/requirements.txt
$ make test
To understand what test options are available simply run:
$ make help
For example, to run the tests strictly desigined for TS.ADD command, follow these steps:
$ make test TEST=test_ts_add.py
Read the docs at http://redistimeseries.io
Got questions? Feel free to ask at the RedisTimeSeries forum.
RedisTimeSeries is licensed under the Redis Source Available License 2.0 (RSALv2) or the Server Side Public License v1 (SSPLv1).