Buying snapshot
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| Decision point | What PostgreSQL states |
|---|---|
License | Open source. Copyright and license terms are in the COPYRIGHT file of the source distribution. |
Installation | Download from postgresql.org/download, or build from source by following the installation guide in the documentation. |
Latest releases | 18.6, 17.11, 16.15, 15.19 and 14.24, all dated 2026-08-13. |
End of fixes | PostgreSQL 14 stops receiving fixes on November 12, 2026. The project suggests production users plan an upgrade to a newer, supported version. |
Next major version | PostgreSQL 19 RC 1, released 2026-10-15. The project does not advise running rc versions in production. |
Community help | Mailing lists (a PostgreSQL community account is needed to manage a subscription), events, local user groups and training sessions. |
Contributing changes | Patches go through the Submitting a Patch process on the PostgreSQL wiki. The GitHub repository is a mirror and does not take pull requests. |
Our take
Choose PostgreSQL if you want an open-source relational database that keeps integrity rules in the database, and your team can own installation, version upgrades and the choice of extensions. If no one on the team can own that work, do not run it alone.
Evaluate PostgreSQL
Popular comparisons
See all 6 PostgreSQL comparisons
Where it stands out
Long track record. PostgreSQL has over 35 years of active development. The project says this has earned it a strong reputation for reliability, feature robustness and performance. For a system of record that should outlive several applications, that history matters.
Integrity rules in SQL. It supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries and triggers. Teams can enforce relationships and rules in one place instead of in each application.
Extensible core. User-defined types and functions let teams add their own data types and logic, and the distribution includes C language bindings.
Third-party tools around the core. On 2026-10-26 the postgresql.org news listed new releases of pg_ivm 1.17, HypoPG 1.4.4 and pg_hdr_histogram 1.0.0 (exact percentiles), each from its own developers. It also lists pgrecon, an open-source tool for Oracle to PostgreSQL migration assessment and schema conversion.
Product screenshot
Trade-offs to weigh
Major upgrades are your job. The end-of-fixes date above is a deadline for your team, not for a vendor. Budget time to test and move to a newer major version, not only to apply minor releases.
Check who maintains each add-on tool. Your production setup may depend on tools outside the core project, such as SafeGrd for PostgreSQL backups that are restored and checked on a schedule. Confirm each one's upkeep before you rely on it.
New features wait for the final release. Teams that want PostgreSQL 19 features can test them on their own workloads now, but should plan production use after general availability.
Public signals
About these signals
Verified factual signals from public sources. They indicate observable activity or interest, not total adoption, product quality, or cost.
861 GitHub commits 90d22.8k GitHub stars0 vulnerabilities across 2 packagesOpenSSF score 6.1/10
See all signals from 9 sources
npm · pg@8.23.1 · PyPI · psycopg2@2.9.13
Alternatives to PostgreSQL
The reviewed substitutes for PostgreSQL among the relational databases, and what would make each one the better answer.
Direct alternatives
Reviewed substitutes: products bought for the same job, where a team picks one.
- MySQL
- The two default open-source relational databases. The choice is made once, for the same application workload.
Other approaches
A different approach to the same problem. Each substitutes only for the workload named beside it.
- DuckDB
- DuckDB and PostgreSQL can both run SQL queries for analysis on a team's data. PostgreSQL is a general-purpose relational database server built for transactions and many concurrent users. DuckDB is an in-process columnar engine, so it is the faster pick when the job is scanning and aggregating large tables or files for analytics.Applies to: When the job is analytical queries over a team's data rather than serving an application.
- MongoDB
- A relational and a document-oriented approach to the same application data. The data model decides, not a feature race.Applies to: Application workloads whose schema is either stable enough for relations or variable enough for documents.
- Neo4j
- PostgreSQL can carry graph-shaped data with recursive queries, so it substitutes for Neo4j on lighter connected-data work — not universally.Applies to: Connected-data workloads whose traversals are shallow and bounded. Deep or variable-length traversal is where the graph database is not replaceable.
- Snowflake
- An operational relational database and an analytical warehouse are built for different query shapes, and teams reporting from the operational database do compare them when reports start to slow the application down. The decision is whether analytics needs its own store.Applies to: Whether reporting can run on the operational database or needs a separate analytical store.