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Key Concepts

To understand how GreptimeDB manages and serves its data, you need to know about these building blocks of GreptimeDB.

Database​

Similar to database in relational databases, a database is the minimal unit of data container, within which data can be managed and computed. Users can use the database to achieve data isolation, creating a tenant-like effect.

Time-Series Table​

GreptimeDB designed time-series table to be the basic unit of data storage. It is similar to a table in a traditional relational database, but requires a timestamp column(We call it time index). The table holds a set of data that shares a common schema, it's a collection of rows and columns:

  • Column: a vertical set of values in a table, GreptimeDB distinguishes columns into time index, tag and field.
  • Row: a horizontal set of values in a table.

It can be created using SQL CREATE TABLE, or inferred from the input data structure using the auto-schema feature. In a distributed deployment, a table can be split into multiple partitions that sit on different datanodes.

For more information about the data model of the time-series table, please refer to Data Model.

Table Region​

Each partition of distributed table is called a region. A region may contain a sequence of continuous data, depending on the partition algorithm. Region information is managed by Metasrv. It's completely transparent to users who send write requests or queries.

Data Types​

Data in GreptimeDB is strongly typed. Auto-schema feature provides some flexibility when creating a table. Once the table is created, data of the same column must share common data type.

Find all the supported data types in Data Types.

Index​

The index is a performance-tuning method that allows faster retrieval of records. GreptimeDB uses the inverted index to accelerate queries.

View​

The view is a virtual table that is derived from the result set of a SQL query. It contains rows and columns just like a real table, but it doesn’t store any data itself. The data displayed in a view is retrieved dynamically from the underlying tables each time the view is queried.

Flow​

A flow in GreptimeDB refers to a continuous aggregation process that continuously updates and materializes aggregated data based on incoming data.