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CeresDB is a high-performance, distributed, schema-less, cloud native time-series database that can handle both time-series and analytics workloads.

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HoraeDB

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HoraeDB is a high-performance, distributed, cloud native time-series database.

Documentation

Quick Start

Run with Docker

Run HoraeDB standalone Server

docker run -d --name horaedb-server \
  -p 8831:8831 \
  -p 3307:3307 \
  -p 5440:5440 \
  ghcr.io/apache/horaedb-server:nightly-20231222-f57b3827

Run HoraeDB cluster with two horaedb-server node and one horaemeta-server node.

docker compose -f docker/docker-compose.yaml up

Run from source code

See details here.

Create Table and Write/Read data

Create Table.

curl --location --request POST 'http://127.0.0.1:5440/sql' \
-d '
CREATE TABLE `demo` (
    `name` string TAG,
    `value` double NOT NULL,
    `t` timestamp NOT NULL,
    timestamp KEY (t))
ENGINE=Analytic
  with
(enable_ttl="false")
'

Write data with SQL.

curl --location --request POST 'http://127.0.0.1:5440/sql' \
-d '
INSERT INTO demo (t, name, value)
    VALUES (1702224000000, "horaedb", 100)
'

Read data with SQL.

curl --location --request POST 'http://127.0.0.1:5440/sql' \
-d '
SELECT * FROM `demo`
'

Drop table.

curl --location --request POST 'http://127.0.0.1:5440/sql' \
-d '
Drop TABLE `demo`
'

Contributing

Any contribution is welcome!

Discuss at dev mailing list (subscribe / unsubscribe / archives)

Send request to dev@horaedb.apache.org to join Horadb slack channel.

Read our Contributing Guide and make your first contribution!

Acknowledgment

When develop HoraeDB, we benefit a lot from several other open source projects, such as influxdb_iox, tikv etc, thanks for their awesome work.

In our production usage, we heavily use OceanBase as implementation of both WAL and ObjectStorage, and OceanBase team help us maintain stability of our cluster, thanks for their kindly support.

License

HoraeDB is under Apache License 2.0.

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CeresDB is a high-performance, distributed, schema-less, cloud native time-series database that can handle both time-series and analytics workloads.

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