This post will go through how to interact with an PostgreSQL database in Go, and how to make your application production ready when it comes to connecting and querying your database server.

banner image

If you just want to see the example code, you can view it on Github

The “database/sql” Standard Library

Let’s go through the architecture of the standard library package used for interacting with SQL databases in Go: database/sql.

This package gives us a common interface that can be used to connect and query different types of databases. This interface is implemented by the driver for each database type:

application code talks to sql package interface, which then uses the driver to call the database instance

Our application code uses the interface provided by the database/sql standard library. The driver implements this interface to undertake the actual interaction with the database.

This means that we can use the same interface for interacting with a number of popular databases. Let’s see how we can make use of a driver for connecting to a PostgreSQL database.

Installing the Database Driver

The list of all compatible drivers can be found on the official Go Wiki page.

Since we’re using Postgres for this example, we’ll be using the pgx driver.

We can create a new directory for our code and initialize a new Go module:

mkdir go-sql-database-example && cd go-sql-database-example
# you can name the module according to your directory
go mod init

Next, install the pgx driver and create a main.go file:

go get
touch main.go

Creating a Test Database

Let’s create a test database and table that we can use for illustration.

If you’ve installed Postgres, we can create the database and tables in the interactive shell using the psql command:

CREATE DATABASE bird_encyclopedia;
\c bird_encyclopedia

  bird VARCHAR(256),
  description VARCHAR(1024)

INSERT INTO birds (bird , description) VALUES 
('pigeon', 'common in cities'),
('eagle', 'bird of prey');

Opening a Database Connection

We can now use the installed driver to open and verify a new connection with our database.

// file: main.go
package main

import (

	// Importing pgx v5 for PostgreSQL database operations. The pgx package is used
	// directly for database connection and operations, replacing the standard database/sql package.
	_ ""

func main() {
	// The `sql.Open` function opens a new `*sql.DB` instance. We specify the driver name
	// and the URI for our database. Here, we're using a Postgres URI from an environment variable
	db, err := sql.Open("pgx", os.Getenv("DATABASE_URL"))
	if err != nil {
		log.Fatalf("could not connect to database: %v", err)

	// To verify the connection to our database instance, we can call the `Ping`
	// method with a context. If no error is returned, we can assume a successful connection
	if err := db.PingContext(context.Background()); err != nil {
		log.Fatalf("unable to reach database: %v", err)
	fmt.Println("database is reachable")
  • If you’re running the database on your local machine, you can set the DATABASE_URL environment variable to postgresql://localhost:5432/bird_encyclopedia before running the code.
  • The db variable in this example is an instance of *sql.DB which represents the reference to our database instance
  • Although pgx provides its own interface for interacting with PostgreSQL, we are utilizing the pgx adapter with the database/sql interface. This approach allows us to leverage the standard database/sql package’s features while still benefiting from some of the performance and advanced features of pgx.

Executing SQL Queries

There are multiple ways to execute queries depending on the use case. Let’s go through some of them:

We can use the db.QueryRow method when we require a single entry from our table (For example, fetching an entry based on its unique key).

First, let’s define a struct to represent the results of each query:

type Bird struct {
	Species     string
	Description string

Let’s use the QueryRow method to fetch the first entry in our birds table:

// `QueryRow` always returns a single row from the database
row := db.QueryRow("SELECT bird, description FROM birds LIMIT 1")
// Create a new `Bird` instance to hold our query results
bird := Bird{}
// the retrieved columns in our row are written to the provided addresses
// the arguments should be in the same order as the columns defined in
// our query
if err := row.Scan(&bird.Species, &bird.Description); err != nil {
	log.Fatalf("could not scan row: %v", err)
fmt.Printf("found bird: %+v\n", bird)

This will give us the following output:

found bird: {Species:pigeon Description:common in cities}

If we want to query multiple rows, we can use the Query method, which returns a Rows instance instead of a single row like the previous example.

rows, err := db.Query("SELECT bird, description FROM birds limit 10")
if err != nil {
	log.Fatalf("could not execute query: %v", err)
// create a slice of birds to hold our results
birds := []Bird{}

// iterate over the returned rows
// we can go over to the next row by calling the `Next` method, which will
// return `false` if there are no more rows
for rows.Next() {
	bird := Bird{}
	// create an instance of `Bird` and write the result of the current row into it
	if err := rows.Scan(&bird.Species, &bird.Description); err != nil {
		log.Fatalf("could not scan row: %v", err)
	// append the current instance to the slice of birds
	birds = append(birds, bird)
// print the length, and all the birds
fmt.Printf("found %d birds: %+v", len(birds), birds)


found 2 birds: [{Species:pigeon Description:common in cities} {Species:eagle Description:bird of prey}]

Adding Query Parameters

Query parameters are the standard and secure way to add variables to your queries.

Most of the time, we need to modify our SQL queries according to variables defined in our code.

We can use the Query and QueryRow methods to add variables in our code as query parameters. To illustrate, let’s add a WHERE clause to get information about the eagle:

birdName := "eagle"
// For Postgres, parameters are specified using the "$" symbol, along with the index of
// the param. Variables should be added as arguments in the same order
// The sql library takes care of converting types from Go to SQL based on the driver
row := db.QueryRow("SELECT bird, description FROM birds WHERE bird = $1 LIMIT $2", birdName, 1)

// the code to scan the obtained row is the same as before

Note: The symbols used for query params depends on the database you’re using. For example, we have to use the ? symbol in MySQL instead of $ which is specific to Postgres

Executing Writes - INSERT, UPDATE, and DELETE

As opposed to reads (SELECT queries), there are no returned rows after writing to a database.

Instead, the database returns information about the executed query, like the number of rows returned.

With the sql library, we can make use of the Exec method to execute write queries. Let’s see how we can use this to insert a new entry into the birds table:

// sample data that we want to insert
newBird := Bird{
	Species:     "rooster",
	Description: "wakes you up in the morning",
// the `Exec` method returns a `Result` type instead of a `Row`
// we follow the same argument pattern to add query params
result, err := db.Exec("INSERT INTO birds (bird, description) VALUES ($1, $2)", newBird.Species, newBird.Description)
if err != nil {
	log.Fatalf("could not insert row: %v", err)

// the `Result` type has special methods like `RowsAffected` which returns the
// total number of affected rows reported by the database
// In this case, it will tell us the number of rows that were inserted using
// the above query
rowsAffected, err := result.RowsAffected()
if err != nil {
	log.Fatalf("could not get affected rows: %v", err)
// we can log how many rows were inserted
fmt.Println("inserted", rowsAffected, "rows")


inserted 1 rows

You can still execute write queries using Query or QueryRow, but the Exec method saves us some of the work for common operations, like getting the affected rows

Prepared Statements: Enhancing Performance and Security

Prepared statements are a crucial aspect of database interactions, offering both performance and security benefits. Let’s delve into how to utilize them effectively:

What are Prepared Statements?

A prepared statement is a pre-compiled SQL query stored on the database server. When you execute a prepared statement, you’re essentially reusing the compiled query plan, reducing the overhead of parsing and planning the query repeatedly.


  • Performance: Reduced query execution time, especially for frequently executed queries.
  • Security: Prepared statements effectively prevent SQL injection vulnerabilities, as the query structure is defined separately from user-supplied values.

Using Prepared Statements in Go:

  1. Preparation: You use the db.Prepare() method to create a prepared statement.

  2. Execution: You execute the prepared statement using stmt.Exec() for write operations (INSERT, UPDATE, DELETE) or stmt.Query() for read operations (SELECT).


// 1. Prepare the statement
stmt, err := db.Prepare("SELECT bird, description FROM birds WHERE bird = $1")
if err != nil {
defer stmt.Close() // Important to close prepared statements

// 2. Execute the statement with a parameter
var bird Bird
err = stmt.QueryRow("eagle").Scan(&bird.Species, &bird.Description)
if err != nil {
fmt.Printf("result: %+v", bird)


result: {Species:eagle Description:bird of prey}

In this example, the query SELECT bird, description FROM birds WHERE bird = $1 is prepared once. When stmt.QueryRow("eagle") is executed, the value “eagle” is safely passed as a parameter to the prepared statement.

Of course, the drawback of prepared statements is that they are specific to the query structure. If you have a dynamic query structure, you might not be able to use prepared statements. But in general, its always a good idea to have prepared statements for queries that are executed frequently.

Connection Pooling - Timeouts and Max/Idle Connections

This section will go over how to best manage the network connections that we open to our database server.

The database server exists as a separate process from our Go application. All queries that we execute have to go over a TCP connection that we open with the database.

application sends queries to database over a single TCP connection

For production applications, we can have a “pool” of simultaneous connections made to the database server. This allows us to run multiple queries concurrently.

There are various options that we can use to configure the database connection pool in our application:

  • Maximum Open Connections are the maximum number of parallel connections that can be made to the database at any time.
  • Maximum Idle Connections are the maximum number of connections that can be inactive at any time. A connection is idle, if no queries are being executed on it. This can happen if the number of queries being executed are less than the current pool of connections can handle.
  • Idle Connection Timeout is the maximum time for which any given connection can be idle. After this time had elapsed, the connection to the database will be closed.
  • Connection Lifetime is the maximum amount of time that a connection can be open (regardless of whether it’s idle or not).

application can maintain a pool of multiple connections with the database, some of them are active (queries currently running), some are idle

By configuring these options, we can set the behavior of our connection pool. The *sql.DB instance gives us various methods to set these options:

db, err := sql.Open("pgx", "postgresql://localhost:5432/bird_encyclopedia")
if err != nil {
	log.Fatalf("could not connect to database: %v", err)

// Maximum Idle Connections
// Maximum Open Connections
// Idle Connection Timeout
db.SetConnMaxIdleTime(1 * time.Second)
// Connection Lifetime
db.SetConnMaxLifetime(30 * time.Second)

The exact values of these options depend on the overall throughput and average query execution time of our application, but in general:

  1. It’s good to have a small percentage of your connections be idle to provide for sudden spikes in query throughput
  2. We should set the maximum number of open connections based on the network capacity of our database server and application servers, the lesser of which will be the limiting factor.

If you open too many connections, you might run into network congestion issues, and if you open too few, you might run into query timeouts in case there are too many queries coming in at once. So make sure to monitor the performance of your application and adjust these values accordingly.

Query Timeouts - Using Context Cancellation

If a query is running for longer than expected, we can cancel it using a context variable. Cancelling a query is especially important in production applications, where we want to prevent queries from running indefinitely, and blocking other queries from running.

Context based cancellation is a popular method of prematurely exiting from running processes. The sql library provides helper methods to use existing context variables to determine when to cancel a query.

Let’s see how we can use context timeouts to stop a query midway:

// create a parent context
ctx := context.Background()
// create a context from the parent context with a 300ms timeout
ctx, _ = context.WithTimeout(ctx, 300*time.Millisecond)
// The context variable is passed to the `QueryContext` method as
// the first argument
// the pg_sleep method is a function in Postgres that will halt for
// the provided number of seconds. We can use this to simulate a 
// slow query
_, err = db.QueryContext(ctx, "SELECT * from pg_sleep(1)")
if err != nil {
	log.Fatalf("could not execute query: %v", err)

Running this code should give us this error message:

2024/07/20 11:29:32 could not execute query: timeout: context deadline exceeded
exit status 1

In production applications, it is always preferred to have timeouts for all queries: A sudden increase in throughput or a network issue can lead to queries slowing down by orders of magnitude.

Slow queries block the connections that they are running on, preventing other queries from running on them. We should always set a timeout after which to cancel a running query, to unblock connections in these cases.

Context with Value: Enhanced Logging and Tracing

Context in Go is incredibly powerful. Besides deadlines and cancellation, we can use it to store request-scoped values. This is invaluable for logging and tracing database interactions.

By associating a unique request ID with each request, we can easily follow the flow of operations in our logs.

For example, if we have a web server that handles multiple requests concurrently, we can generate a unique request ID for each request and store it in the context. This request ID can then be used to log all operations related to that request:

func handleRequest(w http.ResponseWriter, r *http.Request) {
  // Generate a unique request ID
	requestID := uuid.New().String() 

  // Add request ID to the context
	ctx := context.WithValue(r.Context(), "request_id", requestID) 

  // ... Your database interactions using this context
	fetchBird(ctx, db, "eagle")

func fetchBird(ctx context.Context, db *sql.DB, name string) {
	requestID := ctx.Value("request_id").(string)
	// ... Log the request ID along with your database operations
	log.Printf("[%s] Fetching bird: %s", requestID, name) 

	// ... (Rest of the database query logic)

Now, each log message related to a specific request will carry the same request_id, making debugging and tracing a breeze.

Going Forward

This post went over some of the common methods and practices to make your database production ready, but we are still just scratching the surface.

There are numerous ways you can improve the performance and robustness of your application and database in production:

  1. You can use DBStats to monitor the state of your database connections.
  2. Make use of transactions if your queries are dependent on each others results.

Of course, you should make sure to look at your applications requirements in terms of scale and performance before designing it’s architecture.

What practices do you use when interacting with a database in your application? Let me know in the comments!

You can see the full code for all the examples in this post on Github