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GreptimeDB consists of the following key components:

  • Frontend that exposes read and write service in various protocols, forwards requests to Datanode.
  • Datanode is responsible for storing data to persistent storage such as local disk or object storage in the cloud such as AWS S3, Azure Blob Storage etc.
  • Metasrv server that coordinates the operations between the Frontend and Datanode.



To better understand GreptimeDB, a few concepts need to be introduced:

  • A table is where user data is stored in GreptimeDB. A table has a schema and a totally ordered primary key. A table is split into segments called region by its partition key.
  • A region is a contiguous segment of a table, and also could be regarded as a partition in some relational databases. A region could be replicated on multiple datanode and only one of these replicas is writable and can serve write requests, while any replica can serve read requests.
  • A datanode stores and serves region to frontends. One datanode can serve multiple regions and one region can be served by multiple datanodes.
  • The metasrv stores the metadata of the cluster, such as tables, datanodes, regions of each table, etc. It also coordinates frontends and datanodes.
  • The frontend has a catalog implementation, which fetches the metadata from metasrv, tells which region of a table is served by which datanode.
  • A frontend is a stateless service that serves requests from client. It acts as a proxy to forward read and write requests to corresponding datanode, according to the mapping from catalog.
  • A timeseries of a table is identified by its primary key. Each table must have a timestamp column, as GreptimeDB is a timeseries database. Data in table will be sorted by its primary key and timestamp, but the actual order is implementation specific and may change in the future.

How it works

Interactions between components

Before diving into each component, let's take a high level view of how the database works.

  • Users can interact with the database via various protocols, such as ingesting data using InfluxDB line protocol, then exploring the data using SQL or PromQL. The frontend is the component users or clients connect to and operate, thus hide datanode and metasrv behind it.
  • Assumes a user uses the HTTP API to insert data into the database, by sending a HTTP request to a frontend instance. When the frontend receives the request, it then parses the request body using corresponding protocol parser, and finds the table to write to from a catalog manager based on metasrv.
  • The frontend relies on a push-pull strategy to cache metadata from metasrv, thus it knows which datanode, or more precisely, the region a request should be sent to. A request may be split and sent to multiple regions, if its contents need to be stored in different regions.
  • When datanode receives the request, it writes the data to the region, and then sends response back to the frontend. Writing to the region will then write to the underlying storage engine, which will eventually put the data to persistent device.
  • Once frontend has received all responses from the target datanodes, it then sends the result back to the user.

For more details on each component, see the following guides: