vchord
vchord : Vector database plugin for Postgres, written in Rust
Overview
| ID | Extension | Package | Version | Category | License | Language |
|---|---|---|---|---|---|---|
| 1810 | vchord | vchord | 1.1.1 | RAG | AGPL-3.0 | Rust |
| Attribute | Has Binary | Has Library | Need Load | Has DDL | Relocatable | Trusted |
|---|---|---|---|---|---|---|
--sLd-r | No | Yes | Yes | Yes | yes | no |
| Relationships | |
|---|---|
| Requires | vector |
| See Also | vectorscale vectorize vchord_bm25 pg_tiktoken pgml pg_bestmatch pg_similarity smlar |
Packages
| Type | Repo | Version | PG Major Compatibility | Package Pattern | Dependencies |
|---|---|---|---|---|---|
| EXT | PIGSTY | 1.1.1 | 18 17 16 15 14 | vchord | vector |
| RPM | PIGSTY | 1.1.1 | 18 17 16 15 14 | vchord_$v | pgvector_$v |
| DEB | PIGSTY | 1.1.1 | 18 17 16 15 14 | postgresql-$v-vchord | postgresql-$v-pgvector |
| Linux / PG | PG18 | PG17 | PG16 | PG15 | PG14 |
|---|---|---|---|---|---|
el8.x86_64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
el8.aarch64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
el9.x86_64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
el9.aarch64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
el10.x86_64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
el10.aarch64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
d12.x86_64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
d12.aarch64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
d13.x86_64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
d13.aarch64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
u22.x86_64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
u22.aarch64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
u24.x86_64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
u24.aarch64 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 | PIGSTY 1.1.1 |
Source
pig build pkg vchord;# build rpm/debInstall
Make sure PGDG and PIGSTY repo available:
pig repo add pgsql -u # add both repo and update cacheInstall this extension with pig:
pig install vchord;# install via package name, for the active PG version pig install vchord -v 18; # install for PG 18 pig install vchord -v 17; # install for PG 17 pig install vchord -v 16; # install for PG 16 pig install vchord -v 15; # install for PG 15 pig install vchord -v 14; # install for PG 14Config this extension to shared_preload_libraries:
shared_preload_libraries = 'vchord';Create this extension with:
CREATE EXTENSION vchord CASCADE; -- requires vectorUsage
- https://github.com/tensorchord/VectorChord
- Launch Blog: VectorChord: Store 400k Vectors for $1 in PostgreSQL
Add this extension to shared_preload_libraries in postgresql.conf
CREATE EXTENSION vchord CASCADE;Create Index on embedding:
CREATE INDEX ON gist_train USING vchordrq (embedding vector_l2_ops) WITH (options = $$ residual_quantization = true [build.internal] lists = [4096] spherical_centroids = false build_threads = 8 $$);Docs
Query
The query statement is exactly the same as pgvector. VectorChord supports any filter operation and WHERE/JOIN clauses like pgvecto.rs with VBASE.
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;Supported distance functions are:
<->- L2 distance<#>- (negative) inner product<=>- cosine distance
Due to the limitation of postgresql query planner, we cannot support the range query like
SELECT embedding <-> '[3,1,2]' as distance WHERE distance < 0.1 ORDER BY distancedirectly.
To query vectors within a certain distance range, you can use the following syntax.
-- Query vectors within a certain distance range -- sphere(center, radius) means the vectors within the sphere with the center and radius, aka range query -- <<->> is L2 distance, <<#>> is inner product, <<=>> is cosine distance SELECT vec FROM t WHERE vec <<->> sphere('[0.24, 0.24, 0.24]'::vector, 0.012) Query Performance Tuning
You can fine-tune the search performance by adjusting the probes and epsilon parameters:
-- Set probes to control the number of lists scanned. -- Recommended range: 3%–10% of the total `lists` value. SET vchordrq.probes = 100; -- Set epsilon to control the reranking precision. -- Smaller value means less rerank for faster speed, larger value for higher recall. -- Recommended range: 0.0–4.0. Default value is 1.9. SET vchordrq.epsilon = 1.9;And for postgres’s setting
-- If using SSDs, set `effective_io_concurrency` to 200 for faster disk I/O. SET effective_io_concurrency = 200; -- Disable JIT (Just-In-Time Compilation) as it offers minimal benefit (1–2%) -- and adds overhead for single-query workloads. SET jit = off; -- Allocate at least 25% of total memory to `shared_buffers`. -- For disk-heavy workloads, you can increase this to up to 90% of total memory. You may also want to disable swap with network storage to avoid io hang. -- Note: A restart is required for this setting to take effect. ALTER SYSTEM SET shared_buffers = '8GB';Indexing prewarm
To prewarm the index, you can use the following SQL. It will significantly improve performance when using limited memory.
-- vchordrq_prewarm(index_name::regclass) to prewarm the index into the shared buffer SELECT vchordrq_prewarm('gist_train_embedding_idx'::regclass);Index Build Time
Index building can be parallelized using build_threads in the index options and PostgreSQL settings. Optimize parallelism using the following settings:
-- Set this to the number of CPU cores available for parallel operations. SET max_parallel_maintenance_workers = 8; SET max_parallel_workers = 8; -- Adjust the total number of worker processes. -- Note: A restart is required for this setting to take effect. ALTER SYSTEM SET max_worker_processes = 8;Indexing Progress
You can check the indexing progress by querying the pg_stat_progress_create_index view.
SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;External Index Precomputation
Unlike pure SQL, an external index precomputation will first do clustering outside and insert centroids to a PostgreSQL table. Although it might be more complicated, external build is definitely much faster on larger dataset (>5M).
To get started, you need to do a clustering of vectors using faiss, scikit-learn or any other clustering library.
The centroids should be preset in a table of any name with 3 columns:
- id(integer): id of each centroid, should be unique
- parent(integer, nullable): parent id of each centroid, should be NULL for normal clustering
- vector(vector): representation of each centroid,
pgvectorvector type
And example could be like this:
-- Create table of centroids CREATE TABLE public.centroids (id integer NOT NULL UNIQUE, parent integer, vector vector(768)); -- Insert centroids into it INSERT INTO public.centroids (id, parent, vector) VALUES (1, NULL, '{0.1, 0.2, 0.3, ..., 0.768}'); INSERT INTO public.centroids (id, parent, vector) VALUES (2, NULL, '{0.4, 0.5, 0.6, ..., 0.768}'); INSERT INTO public.centroids (id, parent, vector) VALUES (3, NULL, '{0.7, 0.8, 0.9, ..., 0.768}'); -- ... -- Create index using the external centroid table CREATE INDEX ON gist_train USING vchordrq (embedding vector_l2_ops) WITH (options = $$ [build.external] table = 'public.centroids' $$);To simplify the workflow, we provide end-to-end scripts for external index pre-computation, see scripts.
Limitations
- Architecture Compatibility: The fast-scan kernel is optimized for x86_64 architectures. While it runs on aarch64, performance may be lower.
Build
Building this extension requires clang-17+
Which is available on EL 8/9, Ubuntu 24.04 directly, but require manual installation on Ubuntu 22.04 / Debian 12.
For example, install clang-18 on Ubuntu 22 / Debian 12 and set it as the default clang:
curl --proto '=https' --tlsv1.2 -sSf https://apt.llvm.org/llvm.sh | bash -s -- 18 sudo update-alternatives --install /usr/bin/clang clang $(which clang-18) 255