TimescaleDB is an open-source SQL database designed for scalable time-series data. It enables both high ingest rates and real-time analysis queries. It scales by automatically partitioning Hypertable (a single continuous table) into two-dimensional (time and space) proper-sized chunks. Inserts to recent time intervals can be parallelized by placing chunks across cluster or disks based on a specified partition key. Complex queries can be optimized by leveraging metadata of each chunk.
Multi-version Concurrency Control (MVCC) Two-Phase Locking (Deadlock Detection)
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.
Read Uncommitted Read Committed Serializable Repeatable Read
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.
Since TimescaleDB is based on Postgres, it supports Postgres' SQL and PL/pgSQL interfaces. They also provide support for PromQL through a Prometheus adapter.
https://github.com/timescale/timescaledb
https://docs.timescale.com/use-timescale/latest/
Timescale
2017
C++, Delphi, Java, Perl, PL/SQL, Python, Tcl
HP-UX, Linux, OS X, Solaris, Windows