About hypertables

Hypertables are PostgreSQL tables that automatically partition your data by time. You interact with hypertables in the same way as regular PostgreSQL tables, but with extra features that makes managing your time-series data much easier.

In Timescale, hypertables exist alongside regular PostgreSQL tables. Use hypertables to store time-series data. This gives you improved insert and query performance, and access to useful time-series features. Use regular PostgreSQL tables for other relational data.

With hypertables, Timescale makes it easy to improve insert and query performance by partitioning time-series data on its time parameter. Behind the scenes, the database performs the work of setting up and maintaining the hypertable's partitions. Meanwhile, you insert and query your data as if it all lives in a single, regular PostgreSQL table.

Note

Inheritance is not supported for hypertables and may lead to unexpected behavior.

When you create and use a hypertable, it automatically partitions data by time, and optionally by space.

Each hypertable is made up of child tables called chunks. Each chunk is assigned a range of time, and only contains data from that range. If the hypertable is also partitioned by space, each chunk is also assigned a subset of the space values.

Note

When a chunk is created then its creation time is stored in the catalog metadata. This chunk creation time should not be confused with the partition ranges for the data that the chunk contains. Certain functionality can use this chunk creation time metadata in cases where it makes sense.

Each chunk of a hypertable only holds data from a specific time range. When you insert data from a time range that doesn't yet have a chunk, Timescale automatically creates a chunk to store it.

By default, each chunk covers 7 days. You can change this to better suit your needs. For example, if you set chunk_time_interval to 1 day, each chunk stores data from the same day. Data from different days is stored in different chunks.

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Note

Timescale divides time into potential chunk ranges, based on the chunk_time_interval. If data exists for a potential chunk range, that chunk is created.

In practice, this means that the start time of your earliest chunk doesn't necessarily equal the earliest timestamp in your hypertable. Instead, there might be a time gap between the start time and the earliest timestamp. This doesn't affect your usual interactions with your hypertable, but might affect the number of chunks you see when inspecting it.

Chunk size affects insert and query performance. You want a chunk small enough to fit into memory so you can insert and query recent data without reading from disk. However, having too many small and sparsely filled chunks can affect query planning time and compression.

Best practice is to set chunk_time_interval so that prior to processing, one chunk of data takes up 25% of main memory, including the indexes from each active hypertable. For example, if your write approximately 2 GB of data per day to a database with 64 GB of memory, set chunk_time_interval to 1 week. If you write approximately 10 GB of data per day on the same machine, set the time interval to 1 day.

Note

If you use expensive index types, such as some PostGIS geospatial indexes, take care to check the total size of the chunk and its index. You can do so using the chunks_detailed_size function.

For a detailed analysis of how to optimize your chunk sizes, see the blog post on chunk time intervals. To learn how to view and set your chunk time intervals, see the section on changing hypertable chunk intervals.

By default, indexes are automatically created when you create a hypertable. You can prevent index creation by setting the create_default_indexes option to false.

The default indexes are:

• On all hypertables, an index on time, descending
• On hypertables with space partitions, an index on the space parameter and time

Hypertables have some restrictions on unique constraints and indexes. If you want a unique index on a hypertable, it must include all the partitioning columns for the table. To learn more, see the section on creating unique indexes on a hypertable.

You can use the PostgreSQL ANALYZE command to query all chunks in your hypertable. The statistics collected by the ANALYZE command are used by the PostgreSQL planner to create the best query plan. For more information about the ANALYZE command, see the PostgreSQL documentation.

• Create a hypertable
• Read about the benefits and architecture of hypertables