How I use Postgres with Go

The libraries I love to use with Postgres

Most developers will have to interact with SQL at some point in their career, and often nowadays that means working with Postgres. I’ve been using Postgres with Go for a few years now and have found a couple of libraries that work really well together to make the Go Postgres experience productive, safe and fun.

TL:DR; I have created an example repo that puts all of the below into practice:

The libraries cover four separate parts and integrate very well together. First up, lets look at the database driver I use:

Database driver

My Postgres database driver of choice is I often recommend pgx over, having used both in various projects over the years. pq is often the first driver recommended, and it is certainly competent and performant, but it has nothing on the rich type support in pgx/pgtype, and the direct database interface implemented in pgx comes in handy when you need that extra boost of performance in your application. I prefer to use pgx via the stdlib interface most of the time to make the code more familiar with other Go database code, since performance is not always the most important part.

The custom type handling in my example repo shows how to use the postgres types timestamptz and interval from your Go application:

func (tw *timeWrapper) Scan(in interface{}) error {
	var t pgtype.Timestamptz
	err := t.Scan(in)
	if err != nil {
		return err

	tp, err := ptypes.TimestampProto(t.Time)
	if err != nil {
		return err

	*tw = (timeWrapper)(*tp)
	return nil

Next, database setup and migrations:

Setup and migrations

The library I use for setup and migrations is It integrates directly with postgres via the PostgreSQL driver but supports many other databases. I use the Postgres driver together with the go-bindata source driver. This allows me to embed the migrations into the binaries I build, ensuring the database migrations are versioned in SCM together with the logic that is used to interact with the database and also allows distribution of a single static binary. I use go generate or a Makefile to ensure that it’s easy to generate the bindata file. I recommend using a CI script to ensure the file is always up to date with the source files.

For a practical implementation of this, see the migration files and the schema setup code in my example repo:

// version defines the current migration version. This ensures the app
// is always compatible with the version of the database.
const version = 1

func validateSchema(db *sql.DB) error {
	sourceInstance, err := bindata.WithInstance(bindata.Resource(migrations.AssetNames(), migrations.Asset))
	if err != nil {
		return err
	targetInstance, err := postgres.WithInstance(db, new(postgres.Config))
	if err != nil {
		return err
	m, err := migrate.NewWithInstance("go-bindata", sourceInstance, "postgres", targetInstance)
	if err != nil {
		return err
	err = m.Migrate(version) // current version
	if err != nil && err != migrate.ErrNoChange {
		return err
	return sourceInstance.Close()

Next up, the query builder:

Query builder

I use for writing queries. Using fluent interfaces in Go is quite rare, and it rarely works well because of the limitations of Go’s type system. In the case of SQL query building though, I have found it to be an excellent alternative to string interpolation so often seen elsewhere. It makes it trivial to conditionally add WHERE clauses, etc. It doesn’t try to do too much either, simply aiming to allow anything in the SQL standard. Methods like .Suffix, .Prefix and squirrel.Expr can be used to add arbitrary SQL where required.

To use squirrel effectively with Postgres, I recommend creating a StatementBuilder on startup, like the setup method in the example repo does:

sb:     squirrel.StatementBuilder.PlaceholderFormat(squirrel.Dollar).RunWith(db),

This means you can run queries directly on sb, as we can see below.

The AddUser method in the example repo shows a simple insert with squirrel. It explicitly maps the value to the column name, and with a suffix statement we tell Postgres to return the inserted row:

func (d Directory) AddUser(ctx context.Context, req *pbUsers.AddUserRequest) (*pbUsers.User, error) {
	q :=
		"role": (roleWrapper)(req.GetRole()),
		"RETURNING id, role, create_time",

	return scanUser(q.QueryRowContext(ctx))

The ListUsers method shows the use of conditional WHERE clauses in our query:

q :=
    "create_time ASC",

if req.GetCreatedSince() != nil {
    q = q.Where(squirrel.Gt{
        "create_time": (*timeWrapper)(req.GetCreatedSince()),

if req.GetOlderThan() != nil {
    q = q.Where(
            "CURRENT_TIMESTAMP - create_time > $1", (*durationWrapper)(req.GetOlderThan()),

squirrel.Gt is translated to > in the SQL, and it’s trivial to see that it applies to the create_time column. squirrel.Expr is here used to include a raw SQL statement in our WHERE clause. We’re using a custom type to allow us to control the mapping to the Postgres Interval type used in the comparison.

A small comment on where the line between using squirrel and migrate is. squirrel does not even try to let you write any CREATE or DROP statements dynamically, which is where migrate comes in. Use migrate to create and evolve your database schema, and use squirrel for inserts, queries, deletes etc.

Next, the final piece of the puzzle: testing the database layer.


I used to be a frequent user of to test my database interactions. It made it possible to get 100% test coverage and test all the error cases, but the problem is that you have to write both the queries for interacting with the database and the code that is testing that those queries are correct. This either means you write your queries twice, or you copy paste your queries into your test. In either case, you gain no actual confidence that your queries actually do what you want them to, or are even valid SQL.

Therefore, I nowadays recommend the use of to spin up a Postgres container and run your tests against it directly. This is now so fast that these integration type tests can be run almost as quickly as normal unit tests, but they provide you with 100% confidence that your queries are valid SQL and extract the right data from the database. This has frankly revolutionised database testing for me, to the point where I normally don’t bother writing unit tests for my database interactions because it would just be testing rare error cases anyway. The only downside is that it can sometimes be complicated to get this setup working in CI, but I’ve been able to solve it in most cases, see my previous posts.

The example repo comes complete with some tests implemented with dockertest. Most of the magic is in the database setup.


I’ve covered pgx, migrate, squirrel and dockertest, four libraries that together make working with Postgres from Go a real pleasure. I hope this brief post can help you in your own interactions with Postgres from Go. With the exception of pgx, most of the advice here applies to any relational database.

If you enjoyed this blog post, have any questions or input, don’t hesitate to contact me on @johanbrandhorst or under jbrandhorst on the Gophers Slack. I’d love to hear your thoughts!

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