PostgREST serves a fully RESTful API from any existing PostgreSQL
database. It provides a cleaner, more standards-compliant, faster
API than you are likely to write from scratch.
Demo postgrest.herokuapp.com | Read Docs | Watch Video
Try making requests to the live demo server with an HTTP client
such as postman. The structure of the
demo database is defined by
You can use it as inspiration for test-driven server migrations in
your own projects.
docker run -p 3000:3000 \ -e POSTGREST_VERSION=0.3.1.1 \ -e PG_PORT_5432_TCP_ADDR=localhost -e PG_PORT_5432_TCP_PORT=1214 \ -e PG_ENV_POSTGRES_DB=database \ -e PG_ENV_POSTGRES_USER=serioususer \ -e PG_ENV_POSTGRES_PASSWORD=thisisasecret \ -e POSTGREST_SCHEMA=public suzel/docker-postgrest
- Download the binary (latest release)
for your platform.
Invoke like so:
postgrest postgres://postgres:foobar@localhost:5432/my_db \ --port 3000 \ --schema public \ --anonymous postgres \ --pool 200
For more information on valid connection strings see the
TLDR; subsecond response times for up to 2000 requests/sec on Heroku
free tier. (see the load
If you're used to servers written in interpreted languages (or named
after precious gems), prepare to be pleasantly surprised by PostgREST
Three factors contribute to the speed. First the server is written
in Haskell using the
HTTP server (aka a compiled language with lightweight threads).
Next it delegates as much calculation as possible to the database
- Serializing JSON responses directly in SQL
- Data validation
- Combined row counting and retrieval
- Data post in single command (
Finally it uses the database efficiently with the
- Reusing prepared statements
- Keeping a pool of db connections
- Using the PostgreSQL binary protocol
- Being stateless to allow horizontal scaling
Ultimately the server (when load balanced) is constrained by database
performance. This may make it inappropriate for very large traffic
load. To learn more about scaling with Heroku and Amazon RDS see
the performance guide.
supports Postgres clustering for higher performance.
Other optimizations are possible, and some are outlined in the
PostgREST handles authentication (via JSON Web
and delegates authorization to the role information defined in the
database. This ensures there is a single declarative source of truth
for security. When dealing with the database the server assumes
the identity of the currently authenticated user, and for the
duration of the connection cannot do anything the user themselves
couldn't. Other forms of authentication can be built on top
of the JWT primitive. See the docs for more information.
PostgreSQL 9.5 supports true row-level
In previous versions it can be simulated with triggers and
security-barrier views. Because the possible queries to the database
are limited to certain templates using
functions, the trigger workaround does not compromise row-level
For example security patterns see the security
A robust long-lived API needs the freedom to exist in multiple
versions. PostgREST does versioning through database schemas. This
allows you to expose tables and views without making the app brittle.
Underlying tables can be superseded and hidden behind public facing
views. You run an instance of PostgREST per schema and route requests
among them with a reverse proxy such as nginx.
Learn more here.
Rather than writing and maintaining separate docs yourself let the
API explain its own affordances using HTTP. All PostgREST endpoints
respond to the OPTIONS verb and explain what they support as well
as the data format of their JSON payload. RAML support is an upcoming
The project uses HTTP itself to communicate other metadata. For
instance the number of rows returned by an endpoint is reported by -
and limited with - range headers. More about
There are more opportunities for self-documentation listed in Future
Rather than relying on an Object Relational Mapper and custom
imperative coding, this system requires you put declarative constraints
directly into your database. Hence no application can corrupt your
data (including your API server).
The PostgREST exposes HTTP interface with safeguards to prevent
surprises, such as enforcing idempotent PUT requests, and
- Watching endpoint changes with sockets and Postgres pubsub
- Specifying per-view HTTP caching
- Inferring good default caching policies from the Postgres stats collector
- Generating mock data for test clients
- Maintaining separate connection pools per role to avoid "set/reset
role" performance penalty
- Describe more relationships with Link headers
- Depending on accept headers, render OPTIONS as RAML or a
- ... the other issues
The cool logo came from Mikey Casalaina.