ReductStore is a time series database designed specifically for storing and managing large amounts of blob data. It has high performance for writing and real-time querying, making it suitable for edge computing, computer vision, and IoT applications. ReductStore is 100% open source under Mozilla Public License v2.0. It has a simple HTTP API and provides random access to data via a timestamp or time interval. Read more here.

• HTTP(S) API
• Storing and accessing blobs as time series
• Optimized for small files
• Real-time FIFO quota for buckets
• Token authorization
• Labeling and searching
• Embedded Web Console
• Support Linux, MacOS and Windows

The easiest way to start is to use Docker image:

docker run -p 8383:8383 -v ${PWD}/data:/data reduct/store:latest

or you can use cargo:

apt install protobuf-compiler
cargo install reductstore
RS_DATA_PATH=./data reductstore

See Getting Started and Download pages for deail.

ReductStore provides a simple HTTP API, so you could use it with curl:

# Create a bucket
curl -d "{\"quota_type\":\"FIFO\", \"quota_size\":10000}" \
  -X POST \
  "http://127.0.0.1:8383/api/v1/b/my_data"

# Write two records with timestamp 10000 and 20000
curl -d "some_data_1" \
  -X POST \
  --header "x-reduct-label-quality: good" \
  "http://127.0.0.1:8383/api/v1/b/my_data/entry_1?ts=10000"

curl -d "some_data_2" \
  -X POST \
  --header "x-reduct-label-quality: bad" \
  "http://127.0.0.1:8383/api/v1/b/my_data/entry_1?ts=20000"

# Query all records in the bucket (TTL of request 10000s, so you don't need to hurry)
curl "http://127.0.0.1:8383/api/v1/b/my_data/entry_1/q?ttl=10000"

# Take ID from the response and read the data until the end
curl -v "http://127.0.0.1:8383/api/v1/b/my_data/entry_1?q=<ID_FROM_RESPONSE>"

If you don't want to use HTTP API directly, you can use one of the client SDKs:

• Rust Client SDK
• Python Client SDK
• JavaScript Client SDK
• C++ Client SDK

You can use the following tools to administrate ReductStore:

• CLI Client
• Web Console