pg_lake
Overview
| Package | Version | Category | License | Language |
|---|---|---|---|---|
pg_lake | 3.4 | OLAP | Apache-2.0 | C |
| ID | Extension | Bin | Lib | Load | Create | Trust | Reloc | Schema |
|---|---|---|---|---|---|---|---|---|
| 2560 | pg_lake | Yes | Yes | Yes | Yes | No | No | lake |
| 2561 | pg_extension_base | No | Yes | Yes | Yes | No | No | extension_base |
| 2562 | pg_extension_updater | No | Yes | Yes | Yes | No | No | extension_updater |
| 2563 | pg_map | No | Yes | No | Yes | No | No | map_type |
| 2564 | pg_lake_engine | No | Yes | Yes | Yes | No | No | __lake__internal__nsp__ |
| 2565 | pg_lake_iceberg | No | Yes | No | Yes | No | No | lake_iceberg |
| 2566 | pg_lake_table | No | Yes | Yes | Yes | No | No | __pg_lake_table_writes |
| 2567 | pg_lake_copy | No | Yes | Yes | Yes | No | No | pg_catalog |
| Related | pg_lake_copy pg_lake_table pg_ducklake pg_duckdb pg_parquet pg_mooncake duckdb_fdw aws_s3 file_fdw pg_bulkload pg_clickhouse columnar |
|---|
Pigsty packages this release for PG16-18. Configure shared_preload_libraries=pg_extension_base and run the matching PG-major pgduck_server process. RPM supports EL9/EL10 only; EL8 is rejected because OpenSSL 3 is required. DEB supports Debian 12/13 and Ubuntu 22.04/24.04/26.04 on amd64/arm64. DuckDB and Avro are private per PG major. Co-installation with pg_duckdb, pg_mooncake, and duckdb_fdw is file-safe, but overlapping hooks and COPY behavior can be preload-order-sensitive. Extension SQL/control version is 3.4; source and DEB/RPM package version is 3.4.0.
Version
| Type | Repo | Version | PG Ver | Package | Deps |
|---|---|---|---|---|---|
| EXT | PIGSTY | 3.4 | 1817161514 | pg_lake | pg_lake_copy, pg_lake_table |
| RPM | PIGSTY | 3.4.0 | 1817161514 | pg_lake_$v | - |
| DEB | PIGSTY | 3.4.0 | 1817161514 | postgresql-$v-pg-lake | - |
Build
You can build the RPM / DEB packages for pg_lake using pig build:
pig build pkg pg_lake # build RPM / DEB packages
Install
You can install pg_lake directly. First, make sure the PGDG and PIGSTY repositories are added and enabled:
pig repo add pgsql -u # Add repo and update cache
Install the extension using pig or apt/yum/dnf:
pig install pg_lake; # Install for current active PG version
pig ext install -y pg_lake -v 18 # PG 18
pig ext install -y pg_lake -v 17 # PG 17
pig ext install -y pg_lake -v 16 # PG 16
dnf install -y pg_lake_18 # PG 18
dnf install -y pg_lake_17 # PG 17
dnf install -y pg_lake_16 # PG 16
apt install -y postgresql-18-pg-lake # PG 18
apt install -y postgresql-17-pg-lake # PG 17
apt install -y postgresql-16-pg-lake # PG 16
Preload:
shared_preload_libraries = 'pg_extension_base';
Create Extension:
CREATE EXTENSION pg_lake CASCADE; -- requires: pg_lake_copy, pg_lake_table
Usage
Sources:
- Official pg_lake README
- Version 3.4 control file
- Official build and startup guide
- Official project documentation index
- DuckDB secrets manager
pg_lake is the top-level extension for Snowflake’s PostgreSQL lakehouse stack. It installs the table, Iceberg, copy, query-engine, extension-base, and map components needed to query object-store files and create transactional Iceberg tables. The PostgreSQL extensions orchestrate planning and transactions while a separate local pgduck_server process executes vectorized work with DuckDB.
Start the Packaged Stack
Version 3.4 supports PostgreSQL 16 through 18. The PIGSTY RPM and DEB packages install the extension files and a versioned pgduck_server binary, but they do not currently install or auto-start a systemd service. Running CREATE EXTENSION does not start pgduck_server either.
Add pg_extension_base to shared_preload_libraries and restart PostgreSQL:
shared_preload_libraries = 'pg_extension_base'
pgduck_server listens on /tmp/.s.PGSQL.5332 with mode 0770 by default. Run it as the PostgreSQL operating-system user so PostgreSQL can access the socket. Do not start it as an unrelated login user with the bare command.
# Debian/Ubuntu with PostgreSQL 18; use 16 or 17 as appropriate.
PG_LAKE_SERVER=/usr/lib/postgresql/18/bin/pgduck_server
# RHEL-compatible systems use /usr/pgsql-18/bin/pgduck_server.
sudo install -d -o postgres -g postgres -m 0700 \
/var/lib/pg_lake /var/lib/pg_lake/extensions
sudo install -d -o postgres -g postgres -m 0750 /var/cache/pg_lake
sudo -u postgres -H "$PG_LAKE_SERVER" \
--duckdb_database_file_path /var/lib/pg_lake/pgduck_server.db \
--extensions_dir /var/lib/pg_lake/extensions \
--cache_dir /var/cache/pg_lake
This command runs in the foreground and must remain running. Use a service supervisor for production. If you use a dedicated service account instead, make it a member of the postgres group and start the server with --unix_socket_group postgres --unix_socket_permissions 0770.
In another terminal, verify the query engine before creating the extensions:
sudo -u postgres psql -X \
"host=/tmp port=5332 dbname=postgres connect_timeout=2" \
-c 'SELECT version();'
Then create the complete dependency tree in the target database:
CREATE EXTENSION pg_lake CASCADE;
SELECT lake.version();
Configure Object-Store Access
Object-store credentials are resolved by pgduck_server, not by the PostgreSQL backend. AWS and GCP can use their normal credential chains. For a local S3-compatible endpoint such as MinIO, first create the bucket, connect directly to pgduck_server, and create a persistent DuckDB secret:
sudo -u postgres psql -X -h /tmp -p 5332 -d postgres
CREATE PERSISTENT SECRET pglake_object_store (
TYPE S3,
KEY_ID 'access-key',
SECRET 'secret-key',
REGION 'us-east-1',
ENDPOINT 'minio.example.com:9000',
SCOPE 's3://analytics-bucket',
URL_STYLE 'path',
USE_SSL false
);
Connect to PostgreSQL, then choose the managed Iceberg location in the same session that creates the table:
SET pg_lake_iceberg.default_location_prefix =
's3://analytics-bucket/warehouse';
Core Workflows
Create and modify a transactional Iceberg table:
CREATE TABLE measurements (
station_name text NOT NULL,
measured_at timestamptz NOT NULL,
value double precision
) USING iceberg;
INSERT INTO measurements VALUES
('Istanbul', now(), 18.5),
('Haarlem', now(), 9.3);
Import or export Parquet, CSV, or newline-delimited JSON through COPY:
COPY (SELECT * FROM measurements)
TO 's3://analytics-bucket/export/measurements.parquet';
COPY measurements
FROM 's3://analytics-bucket/import/measurements.parquet';
Query files without loading them into PostgreSQL:
CREATE FOREIGN TABLE external_events ()
SERVER pg_lake
OPTIONS (path 's3://analytics-bucket/events/*.parquet');
SELECT count(*) FROM external_events;
Component Index
pg_lake: meta-extension andlake.version().pg_lake_table: data-lake FDW, Iceberg table syntax, file utilities, and table catalogs.pg_lake_iceberg: Iceberg metadata, snapshots, manifests, and catalog integration.pg_lake_copy:COPYinterception for object-store files and lake formats.pg_lake_engine: shared query rewrite, type conversion, cleanup, andpgduck_serverclient layer.pg_extension_base: preload and lifecycle-worker infrastructure.pg_map: generated PostgreSQL map types used for nested lake data.
Operational Caveats
pgduck_serveris required on every PostgreSQL host that can execute lake queries. Keep it supervised and verify its local socket before serving traffic.- The default socket mode is
0770; its owner and group come from the account that startspgduck_server. A mismatched service user causesERROR: could not start query engine. - S3 and compatible credentials are resolved by the DuckDB secrets/credential chain. Grant only the bucket permissions required by the workload.
- The first start may download the DuckDB spatial extension. Ensure the service account has the required network access and writable state/cache directories.
CREATE PERSISTENT SECRETsurvives server restarts, but DuckDB stores it unencrypted under~/.duckdb/stored_secrets. Keep the service account and its home directory stable, restrict permissions, and protect those files as credentials.- The default memory limit is 80 percent of system memory. Set
--memory_limitexplicitly when PostgreSQL andpgduck_servershare a production host. - Iceberg writes create Parquet files per statement. Batch inserts and run regular
VACUUMto avoid many small files. - The PostgreSQL extensions,
pgduck_server, object-store data, and Iceberg catalog form one deployment unit. Back up and upgrade them as separate evidence layers; creating the extension alone does not prove the external services are usable.
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