fenecdb and PostgreSQL

PostgreSQL is a relational database server, and pgvector adds vector types and indexes to it. fenecdb is a document database that runs in a page, in an app, or as a server over HTTP, with full-text and vector search built in.

The facts about PostgreSQL and pgvector on this page were checked on 2026-10-02 against the pages each one links to. fenecdb is at version 0.1.12, and is alpha software.

Which to choose

Choose PostgreSQL with pgvector when

• You want SQL: joins, subqueries, window functions, and every ORM, driver and tool written for it.
• Several clients write at once, in transactions they hold open across statements (MVCC).
• You need what a mature server has: row-level security, logical replication, extensions such as PostGIS, and managed services from many providers.
• Your vectors already live beside relational data you query together.

Choose fenecdb when

• The same database runs in the browser, in a mobile app and on the server, with one query language.
• The client keeps a replica that reads offline and redraws live (Sync).
• Reads and writes over HTTP with nothing in front: on YCSB fenec-server leads PostgreSQL in every workload at 4 and 16 clients, both in Docker (measured below).
• A file per tenant suits your service (Tenants and sharding).
• You search by words, with typos, highlights and facets, and by meaning too: BM25 and rank fusion are built in (Hybrid search).
• Search latency at a million vectors matters (measured below).

Feature by feature

Measured

YCSB's core workloads over a million records, fenec-server over HTTP against PostgreSQL 17, both in Docker on the Mac, durable, operations a second, the median of three runs (every cell, and MongoDB). We measured these on one laptop; the method is below.

• Both in Docker, because the VM's fsync takes a tenth of a millisecond where the Mac's F_FULLFSYNC takes four, and its network a quarter of a millisecond a request: fenec-server on the Mac against PostgreSQL in Docker would compare those, not the two.
• C, reads alone, is where PostgreSQL leads, by 2% at one client, and F by 1%: each server's own part of a read is under 0.02 ms of a 0.29 ms round trip, and the rest is Docker's network, which moves more than that from one day to the next (PostgreSQL's C at one client did 3.66 k on 2026-10-05, its median now 3.14 k). At 4 and 16 clients fenec-server leads every workload; at 16 fenec-server leads C, 18.4 k against 14.8 k.

Then search by meaning: a million 128-dim vectors, fenec-server asked over HTTP and PostgreSQL with pgvector over its own protocol, by the same client program with the same index settings.

• One machine, one run of each side. An Apple M1 MacBook Air; PostgreSQL ran in Docker.
• Every figure, and the 768-dim run, is in Benchmarks.

make ycsb
make pgvector-up      # PostgreSQL 17 with pgvector, the pgvector/pgvector:pg17 image
make scale-bench
make load-bench

Moving from PostgreSQL

fenec import copies a table into a collection over the network, vectors and index included. With --follow it keeps applying the table's changes as they commit.

fenec import postgres://app@db:5432/app --table docs --into articles \
    --index "embed@hnsw(cosine)" --follow

• pgvector's types come across: vector, halfvec and sparsevec keep their dimensions. A numeric needs --cast (Type mapping).
• Following needs wal_level = logical and an integer key. fenec-server --follow serves the mirror as it follows (Serving the mirror).
• Queries are rewritten. fenecdb does not speak SQL or PostgreSQL's protocol, so a pgvector client library cannot connect to it.

The same query in each, and then a nearest-neighbour search:

SELECT title FROM articles
WHERE year >= 2024
ORDER BY published DESC
LIMIT 10;

get articles select title
  where year >= 2024
  order published desc
  limit 10

SELECT title FROM articles
WHERE year >= 2024
ORDER BY embed <=> $1
LIMIT 10;

get articles select title
  where year >= 2024
  near embed $1
  limit 10