pgcolumnar 1.0.0-alpha.3
- This Release
- pgcolumnar 1.0.0-alpha.3
- Date
- Status
- Unstable
- Abstract
- Analytic column storage for PostgreSQL, built as a native table access method
- Description
- pgColumnar is a columnar storage table access method for PostgreSQL, written as a clean-room, MIT-licensed implementation. It reads and writes its own native format, PGCN v1, and supports chunk-group skipping from zone maps and bloom filters, vectorized aggregation, projections, retention, online compaction and reclustering, parallel bulk ingest and export, Apache Arrow and Parquet import and export, Apache Iceberg, and object storage.
- Released By
- jd
- License
- MIT
- Resources
- Special Files
- Tags
Extensions
- pgcolumnar 1.0.0-alpha.3
- Analytic column storage for PostgreSQL, built as a native table access method
Documentation
- ROADMAP
- pgColumnar roadmap
- sql-reference
- SQL reference
- installation
- Installation
- ARCHITECTURE
- pgColumnar architecture
- limitations
- Limitations and compatibility
- requirements
- requirements
- benchmarks
- Benchmarks426 for both the anchored and the infix case.682).** The Iceberg work is on the Iceberg read path. It does not touch the scan,598 gates the gating on projected payload width, a plan-time property the unreliable LIKE '%...%' estimate cannot corrupt.
- PROVENANCE
- Provenance421). ClickBench is licensed CC BY-NC-SA 4.0, not Apache-2.0, which an
- README
- pgColumnar logo
- features
- Features
- roadmap
- Roadmap
- NATIVE_FORMAT_AND_INTERFACE_SPEC
- pgColumnar native format and interface specification
- administration
- Administration
- testing
- Testing
- configuration
- Configuration reference
- best-practices
- Best practices
- user-guide
- User guide
- CHANGELOG
- Changelog852.376 bound and the clustered-index and point-lookup guards in
- how-to
- How-to guides
README
Contents
Analytic column storage for PostgreSQL, built as a native table access method.
Read the documentation at commandprompt.github.io/pgcolumnar
A table created USING pgcolumnar stores its data by column, with per-column
compression, chunk-group skipping, and a vectorized aggregate path. It is for
analytic workloads: large scans, aggregates, and column projections over
append-mostly data.
pgColumnar builds from one source tree on PostgreSQL 15 through 18, with 19
validated against 19beta2, and is
licensed under the MIT License. It is pre-release; the version marker
is 1.0-alpha3, recorded in VERSION. That version is in development and not
tagged; the latest published pre-release is v1.0-alpha2. A table USING pgcolumnar is stored in the
native on-disk format, PGCN v1.
Documentation
The full documentation is published at
commandprompt.github.io/pgcolumnar. The
same pages are in this repository under docs/:
| Features | What pgColumnar provides |
| Installation | Build, load, and create the extension |
| User guide | Create tables, load data, and query |
| Administration | Operate columnar tables in production |
| Configuration | Settings and per-table options |
| SQL reference | The pgcolumnar.* functions |
| Limitations | Compatibility and known constraints |
| Benchmarks | Size and latency numbers |
| Testing | The test suite and version matrix |
| Changelog | Notable changes |
| Architecture | Source map for developers |
Quick start
Build with PGXS against the target server, add the library to
shared_preload_libraries, and restart:
make PG_CONFIG=/path/to/pg_config
make install PG_CONFIG=/path/to/pg_config
shared_preload_libraries = 'pgcolumnar'
Then, in a database:
CREATE EXTENSION pgcolumnar;
CREATE TABLE events (id bigint, ts timestamptz, kind int, payload text)
USING pgcolumnar;
INSERT INTO events
SELECT g, now(), g % 8, 'p' || g
FROM generate_series(1, 1000000) g;
SELECT count(*), avg(kind) FROM events WHERE kind = 3;
See the installation guide for requirements and the user guide for loading and querying.
Independence
pgColumnar is an independent implementation. It is not derived from the source of any other columnar project. Its on-disk format, its metadata catalog and its SQL interface come from published column-store research and from the open Apache Arrow, Parquet and ORC specifications. They are recorded in design/NATIVE_FORMAT_AND_INTERFACE_SPEC.md. The implementation is built from that specification and the public PostgreSQL API, by the clean-room method described in PROVENANCE.md.
License
MIT. See LICENSE.