feat: add support for PolarDB for PostgreSQL HNSW

README.md

@@ -87,6 +87,7 @@ All the database client supported
 | tencent_es               | `pip install vectordb-bench[tencent_es]`    |
 | alisql                   | `pip install vectordb-bench[alisql]`      |
 | polardb                  | `pip install vectordb-bench[polardb]`       |
+| polardb_pg               | `pip install vectordb-bench[pgvector]`      |
 | doris                    | `pip install vectordb-bench[doris]`         |
 | zvec                     | `pip install vectordb-bench[zvec]`          |
 | endee                    | `pip install vectordb-bench[endee]`         |
@@ -116,6 +117,7 @@ Options:
   --help  Show this message and exit.
 
 Commands:
+  polardbpghnsw
   pgvectorhnsw
   pgvectorivfflat
   vectorchordrq
@@ -263,6 +265,47 @@ Options:
   --help                          Show this message and exit.
 ```
 
+### Run polardb_pg from command line
+
+polardb_pg supports HNSW with PQ, SQ4, SQ8, RaBitQ, and Graph Cache.
+This PostgreSQL client is separate from the existing MySQL-compatible PolarDB
+commands and reuses the `pgvector` dependency extra:
+
+```shell
+pip install 'vectordb-bench[pgvector]'
+```
+
+PolarDB-specific internal quantization and Graph Cache options require PolarDB
+vector extension 0.8.3.1 or later. Use `--skip-graph-cache` when Graph Cache is
+not configured on the server.
+
+**Example: Run hnsw index test**
+
+```shell
+vectordbbench polardbpghnsw \
+  --case-type Performance1024D1M \
+  --db-label polardb-pg-rabitq8 \
+  --user-name postgres --password '<password>' \
+  --host localhost --port 5432 --db-name vectordb \
+  --m 16 --ef-construction 256 --ef-search 200 \
+  --quantization rabitq --quantization-nbits 8 \
+  --iterative-scan off --graph-cache
+```
+
+To list the options for polardb_pg, execute
+`vectordbbench polardbpghnsw --help`. The following are some PolarDB-specific
+command-line options.
+
+```text
+  --quantization [pq|sq4|sq8|rabitq]
+  --pq-m INTEGER
+  --train-samples INTEGER
+  --quantization-nbits [1|4|8]
+  --graph-cache / --skip-graph-cache
+  --graph-cache-timeout INTEGER
+  --iterative-scan [off|strict_order|relaxed_order]
+```
+
 ### Run VectorChord (vchordrq) from command line
 
 VectorChord is a PostgreSQL extension for scalable vector similarity search using IVF + RaBitQ indexing.

pyproject.toml

@@ -54,6 +54,9 @@ test = [
     "black",
     "ruff",
     "pytest",
+    "psycopg",
+    "psycopg-binary",
+    "pgvector",
 ]
 restful         = [ "flask" ]
 qdrant          = [ "qdrant-client" ]
@@ -63,7 +66,7 @@ elastic         = [ "elasticsearch" ]
 # For elastic and aliyun_elasticsearch
 
 pgvector        = [ "psycopg", "psycopg-binary", "pgvector" ]
-# for pgvector, pgvectorscale, pgdiskann, alloydb, and lakebase_vector
+# for pgvector, pgvectorscale, pgdiskann, alloydb, lakebase_vector, and PolarDB for PostgreSQL HNSW
 
 pgvecto_rs      = [ "pgvecto_rs[psycopg3]>=0.2.2" ]
 redis           = [ "redis" ]