PgDog – Scale Postgres without changing the app
Hey HN! Lev and Justin here, authors of PgDog (https://pgdog.dev/), a connection pooler, load balancer and database sharder for PostgreSQL. If you build apps with a lot of traffic, you know the first thing to break is the database. We are solving this with a network proxy that works without requiring application code changes or database migrations. Our post from last year: https://news.ycombinator.com/item?id=44099187 The most important update: we are in production. Sharding is used a lot, with direct-to-shard queries (one shard per query) working pretty much…
In plain words
PgDog is a network proxy for PostgreSQL that combines connection pooling, load balancing, and database sharding. It allows applications handling high traffic to scale their databases without modifying application code or running migrations. The tool is designed for developers building traffic-heavy apps and works by intercepting database queries, handling sharding logic transparently, and supporting aggregate functions across shards.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN! Lev and Justin here, authors of PgDog (https://pgdog.dev/), a connection pooler, load balancer and database sharder for PostgreSQL. If you build apps with a lot of traffic, you know the first thing to break is the database. We are solving this with a network proxy that works without requiring application code changes or database migrations. Our post from last year: https://news.ycombinator.com/item?id=44099187 The most important update: we are in production. Sharding is used a lot, with direct-to-shard queries (one shard per query) working pretty much all the time. Cross-shard (or multi-database) queries are still a work in progress, but we are making headway. Aggregate functions like count(), min(), max(), avg(), stddev() and variance() are working, without refactoring the app. PgDog calculates the aggregate in-transit, while transparently rewriting queries to fetch any missing info. For example, multi-database average calculation requires a total count of rows to calculate the original sum. PgDog will add count() to the query, if it’s not there already, and remove it from the rows sent to the app. Sorting and grouping works, including DISTINCT, if the columns(s) are referenced in the result. Over 10 data types are supported, like, timestamp(tz), all integers, varchar, etc. Cross-shard writes, including schema changes (CREATE/DROP/ALTER), are now atomic and synchronized between all shards with two-phase commit. PgDog keeps track of the transaction state internally and will rollback the transaction if the first phase fails. You don’t need to monkeypatch your ORM to use this: PgDog will intercept the COMMIT statement and execute PREPARE TRANSACTION and COMMIT PREPARED instead. Omnisharded tables, a.k.a replicated or mirrored (identical on all shards), support atomic reads and writes. That’s important because most databases can’t be completely sharded and will have some common data on all databases that has to be kept in-sync. Multi-tuple inserts, e.g., INSERT INTO table_x VALUES ($1, $2), ($3, $4), are split by our query rewriter and distributed to their respective shards automatically. They are used by ORMs like Prisma, Sequelize, and others, so those now work without code changes too. Sharding keys can be mutated. PgDog will intercept and rewrite the update statement into 3 queries, SELECT, INSERT, and DELETE, moving the row between shards. If you’re using Citus (for everyone else, Citus is a Postgres extension for sharding databases), this might be worth a look. If you’re like us and prefer integers to UUIDs for your primary keys, we built a cross-shard unique sequence, directly inside PgDog. It uses the system clock (and a couple other inputs), can be called like a Postgres function, and will automatically inject values into queries, so ORMs like ActiveRecord will continue to work out of the box. It’s monotonically increasing, just like a real Postgres sequence, and can generate up to 4 million numbers per second with a range of 69.73 years, so no need to migrate to UUIDv7 just yet. INSERT INTO my_table (id, created_at) VALUES (pgdog.unique_id(), now()); Resharding is now built-in. We can move gigabytes of tables per second, by parallelizing logical replication streams across replicas. This is really cool! Last time we tried this at Instacart, it took over two weeks to move 10 TB between two machines. Now, we can do this in just a few hours, in big part thanks to the work of the core team that added support for logical replication slots to streaming replicas in Postgres 16. Sharding hardly works without a good load balancer. PgDog can monitor replicas and move write traffic to a promoted primary during a failover. This works with managed Postgres, like RDS (incl. Aurora), Azure Pg, GCP Cloud SQL, etc., because it just polls each instance with “SELECT pg_is_in_recovery()”. Primary election is not supported yet, so if you’re self-hosting with Patroni, you should keep it around…
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