History[05][07]

TimescaleDB is in active development by a team of PhDs. It is implemented as a Postgres extension. A single-node version is open-sourced in April, 2017 and a clustered version is currently in private beta release.

Checkpoints[05][08]

It follows PostgreSQL.

Concurrency Control[09][05]

It supports transactions on a per-server basis. Like PostgreSQL, it uses MVCC and Serializable Snapshot Isolation (SSI). It also supports explicit locking with deadlock detection.

Data Model[10]

It follows PostgreSQL

Foreign Keys[10]

It follows PostgreSQL.

Indexes[11][12][13]

It follows PostgreSQL, which has primary, secondary, derived, partial indexes. PostgreSQL supports B-tree, hash, GiST, SP-GiST, GIN, and BRIN indexes, and default is B-tree.

Isolation Levels[14]

It follows PostgreSQL, which supports Read uncommitted, Read committed, Repeatable read, Serializable. Read Committed is the default. They are implemented with MVCC. Note that PostgreSQL's Read Uncommitted is in fact Read Committed.

Joins[10]

It follows PostgreSQL.

Logging[15]

It follows PostgreSQL.

Query Compilation[10]

Not Supported

Query Execution[10]

Query Interface[16]

Since TimescaleDB is based on Postgres, it supports Postgres' SQL and PL/pgSQL interfaces. They also provide support for PromQL through a Prometheus adapter.

Storage Architecture[10]

It follows PostgreSQL

Storage Model[10]

It follows PostgreSQL

Stored Procedures[10]

It follows PostgreSQL.

System Architecture[05]

Like Postgres, TimeScale is a shared-everything DBMS. Each table is partitioned across all space and time intervals.

Views[10]

It follows PostgreSQL.