KSQL the Keep it Simple SQL library

KSQL was created to offer an actually simple and satisfactory tool for interacting with SQL Databases in Golang.

The core idea on KSQL is to offer an easy to use interface, the actual communication with the database is decoupled so we can use KSQL on top of pgx, database/sql and possibly other tools. You can even create you own backend adapter for KSQL which is useful in some situations.

In this README you will find examples for "Getting Started" with the library, for more advanced use-cases please read our Wiki.

Let's start with some Code:

This short example below is a TLDR version for illustrating how easy it is to use KSQL.

You will find more complete examples on the sections below.

package main

import (
	"context"
	"fmt"
	"log"
	"os"

	"github.com/vingarcia/ksql"
	"github.com/vingarcia/ksql/adapters/kpgx"
)

var UsersTable = ksql.NewTable("users", "user_id")

type User struct {
	ID   int    `ksql:"user_id"`
	Name string `ksql:"name"`
	Type string `ksql:"type"`
}

func main() {
	ctx := context.Background()
	db, err := kpgx.New(ctx, os.Getenv("POSTGRES_URL"), ksql.Config{})
	if err != nil {
		log.Fatalf("unable connect to database: %s", err)
	}
	defer db.Close()

	// For querying only some attributes you can
	// create a custom struct like this:
	var count []struct {
		Count string `ksql:"count"`
		Type string `ksql:"type"`
	}
	err = db.Query(ctx, &count, "SELECT type, count(*) as count FROM users WHERE type = $1 GROUP BY type", "admin")
	if err != nil {
		log.Fatalf("unable to query users: %s", err)
	}

	fmt.Println("number of users by type:", count)

	// For loading entities from the database KSQL can build
	// the SELECT part of the query for you if you omit it like this:
	var users []User
	err = db.Query(ctx, &users, "FROM users WHERE type = $1", "admin")
	if err != nil {
		log.Fatalf("unable to query users: %s", err)
	}

	fmt.Println("users:", users)
}

We currently have 4 constructors available, one of them is illustrated above (kpgx.New()), the other ones have the exact same signature but work on different databases, they are:

• kpgx.New(ctx, os.Getenv("DATABASE_URL"), ksql.Config{}) for Postgres, it works on top of pgxpool
• kmysql.New(ctx, os.Getenv("DATABASE_URL"), ksql.Config{}) for MySQL, it works on top of database/sql
• ksqlserver.New(ctx, os.Getenv("DATABASE_URL"), ksql.Config{}) for SQLServer, it works on top of database/sql
• ksqlite3.New(ctx, os.Getenv("DATABASE_URL"), ksql.Config{}) for SQLite3, it works on top of database/sql

The KSQL Interface

The current interface contains the methods the users are expected to use, and it is also used for making it easy to mock the whole library if needed.

This interface is declared in the project as ksql.Provider and is displayed below.

We plan on keeping it very simple with a small number of well thought functions that cover all use-cases, so don't expect many additions:

// Provider describes the KSQL public behavior
//
// The Insert, Patch, Delete and QueryOne functions return `ksql.ErrRecordNotFound`
// if no record was found or no rows were changed during the operation.
type Provider interface {
	Insert(ctx context.Context, table Table, record interface{}) error
	Patch(ctx context.Context, table Table, record interface{}) error
	Delete(ctx context.Context, table Table, idOrRecord interface{}) error

	Query(ctx context.Context, records interface{}, query string, params ...interface{}) error
	QueryOne(ctx context.Context, record interface{}, query string, params ...interface{}) error
	QueryChunks(ctx context.Context, parser ChunkParser) error

	Exec(ctx context.Context, query string, params ...interface{}) (Result, error)
	Transaction(ctx context.Context, fn func(Provider) error) error
}

Using KSQL

In the example below we'll cover all the most common use-cases such as:

1. Inserting records
2. Updating records
3. Deleting records
4. Querying one or many records
5. Making transactions

More advanced use cases are illustrated on their own pages on our Wiki:

• Querying in Chunks for Big Queries
• Avoiding Code Duplication with the Select Builder
• Reusing Existing Structs on Queries with JOINs
• Testing Tools and ksql.Mock

For the more common use-cases please read the example below, which is also available here if you want to compile it yourself.

package main

import (
	"context"
	"fmt"

	"github.com/vingarcia/ksql"
	"github.com/vingarcia/ksql/adapters/ksqlite3"
	"github.com/vingarcia/ksql/nullable"
)

// User ...
type User struct {
	ID   int    `ksql:"id"`
	Name string `ksql:"name"`
	Age  int    `ksql:"age"`

	// This field will be saved as JSON in the database
	Address Address `ksql:"address,json"`
}

// PartialUpdateUser ...
type PartialUpdateUser struct {
	ID      int      `ksql:"id"`
	Name    *string  `ksql:"name"`
	Age     *int     `ksql:"age"`
	Address *Address `ksql:"address,json"`
}

// Address ...
type Address struct {
	State string `json:"state"`
	City  string `json:"city"`
}

// UsersTable informs KSQL the name of the table and that it can
// use the default value for the primary key column name: "id"
var UsersTable = ksql.NewTable("users")

func main() {
	ctx := context.Background()

	// The available adapters are:
	// - kpgx.New(ctx, connURL, ksql.Config{})
	// - kmysql.New(ctx, connURL, ksql.Config{})
	// - ksqlserver.New(ctx, connURL, ksql.Config{})
	// - ksqlite3.New(ctx, connURL, ksql.Config{})
	//
	// For more detailed examples see:
	// - `./examples/all_adapters/all_adapters.go`
	//
	// In this example we'll use sqlite3:
	db, err := ksqlite3.New(ctx, "/tmp/hello.sqlite", ksql.Config{
		MaxOpenConns: 1,
	})
	if err != nil {
		panic(err.Error())
	}
	defer db.Close()

	// In the definition below, please note that BLOB is
	// the only type we can use in sqlite for storing JSON.
	_, err = db.Exec(ctx, `CREATE TABLE IF NOT EXISTS users (
	  id INTEGER PRIMARY KEY,
		age INTEGER,
		name TEXT,
		address BLOB
	)`)
	if err != nil {
		panic(err.Error())
	}

	var alison = User{
		Name: "Alison",
		Age:  22,
		Address: Address{
			State: "MG",
		},
	}
	err = db.Insert(ctx, UsersTable, &alison)
	if err != nil {
		panic(err.Error())
	}
	fmt.Println("Alison ID:", alison.ID)

	// Inserting inline:
	err = db.Insert(ctx, UsersTable, &User{
		Name: "Cristina",
		Age:  27,
		Address: Address{
			State: "SP",
		},
	})
	if err != nil {
		panic(err.Error())
	}

	// Deleting Alison:
	err = db.Delete(ctx, UsersTable, alison.ID)
	if err != nil {
		panic(err.Error())
	}

	// Retrieving Cristina, note that if you omit the SELECT part of the query
	// KSQL will build it for you (efficiently) based on the fields from the struct:
	var cris User
	err = db.QueryOne(ctx, &cris, "FROM users WHERE name = ? ORDER BY id", "Cristina")
	if err != nil {
		panic(err.Error())
	}
	fmt.Printf("Cristina: %#v\n", cris)

	// Updating all fields from Cristina:
	cris.Name = "Cris"
	err = db.Patch(ctx, UsersTable, cris)

	// Changing the age of Cristina but not touching any other fields:

	// Partial update technique 1:
	err = db.Patch(ctx, UsersTable, struct {
		ID  int `ksql:"id"`
		Age int `ksql:"age"`
	}{ID: cris.ID, Age: 28})
	if err != nil {
		panic(err.Error())
	}

	// Partial update technique 2:
	err = db.Patch(ctx, UsersTable, PartialUpdateUser{
		ID:  cris.ID,
		Age: nullable.Int(28), // (just a pointer to an int, if null it won't be updated)
	})
	if err != nil {
		panic(err.Error())
	}

	// Listing first 10 users from the database
	// (each time you run this example a new Cristina is created)
	//
	// Note: Using this function it is recommended to set a LIMIT, since
	// not doing so can load too many users on your computer's memory or
	// cause an Out Of Memory Kill.
	//
	// If you need to query very big numbers of users we recommend using
	// the `QueryChunks` function.
	var users []User
	err = db.Query(ctx, &users, "FROM users LIMIT 10")
	if err != nil {
		panic(err.Error())
	}

	fmt.Printf("Users: %#v\n", users)

	// Making transactions:
	err = db.Transaction(ctx, func(db ksql.Provider) error {
		var cris2 User
		err = db.QueryOne(ctx, &cris2, "FROM users WHERE id = ?", cris.ID)
		if err != nil {
			// This will cause an automatic rollback:
			return err
		}

		err = db.Patch(ctx, UsersTable, PartialUpdateUser{
			ID:  cris2.ID,
			Age: nullable.Int(29),
		})
		if err != nil {
			// This will also cause an automatic rollback and then panic again
			// so that we don't hide the panic inside the KSQL library
			panic(err.Error())
		}

		// Commits the transaction
		return nil
	})
	if err != nil {
		panic(err.Error())
	}
}

Benchmark Comparison

The results of the benchmark are good: they show that KSQL is in practical terms, as fast as sqlx which was our goal from the start.

To understand the benchmark below you must know that all tests are performed using Postgres 12.1 and that we are comparing the following tools:

• KSQL using the adapter that wraps database/sql
• KSQL using the adapter that wraps pgx
• database/sql
• sqlx
• pgx (with pgxpool)
• gorm
• sqlc
• sqlboiler

For each of these tools we are running 3 different queries:

The insert-one query looks like:

INSERT INTO users (name, age) VALUES ($1, $2) RETURNING id

The single-row query looks like:

SELECT id, name, age FROM users OFFSET $1 LIMIT 1

The multiple-rows query looks like:

SELECT id, name, age FROM users OFFSET $1 LIMIT 10

Keep in mind that some of the tools tested (like GORM) actually build the queries internally so the actual code used for the benchmark might differ a little bit from the example ones above.

Without further ado, here are the results:

$ make bench TIME=5s
find . -name go.mod -execdir go mod tidy \;
sqlc generate
go test -bench=. -benchtime=5s
goos: linux
goarch: amd64
pkg: github.com/vingarcia/ksql/benchmarks
cpu: Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz
BenchmarkInsert/ksql/sql-adapter/insert-one-12         	    9358	    630699 ns/op
BenchmarkInsert/ksql/pgx-adapter/insert-one-12         	   10000	    548489 ns/op
BenchmarkInsert/sql/insert-one-12                      	    9601	    631485 ns/op
BenchmarkInsert/sql/prep-stmt/insert-one-12            	   10000	    558009 ns/op
BenchmarkInsert/sqlx/insert-one-12                     	    9688	    637395 ns/op
BenchmarkInsert/sqlx/prep-stmt/insert-one-12           	   10000	    555805 ns/op
BenchmarkInsert/pgxpool/insert-one-12                  	   10000	    558187 ns/op
BenchmarkInsert/gorm/insert-one-12                     	    8671	    690290 ns/op
BenchmarkInsert/sqlc/insert-one-12                     	    9710	    636395 ns/op
BenchmarkInsert/sqlc/prep-stmt/insert-one-12           	   10000	    572243 ns/op
BenchmarkInsert/sqlboiler/insert-one-12                	    9693	    645475 ns/op
BenchmarkQuery/ksql/sql-adapter/single-row-12          	   42440	    139913 ns/op
BenchmarkQuery/ksql/sql-adapter/multiple-rows-12       	   39391	    152663 ns/op
BenchmarkQuery/ksql/pgx-adapter/single-row-12          	   81457	     70102 ns/op
BenchmarkQuery/ksql/pgx-adapter/multiple-rows-12       	   74710	     81578 ns/op
BenchmarkQuery/sql/single-row-12                       	   43040	    139945 ns/op
BenchmarkQuery/sql/multiple-rows-12                    	   41533	    143923 ns/op
BenchmarkQuery/sql/prep-stmt/single-row-12             	   89296	     69676 ns/op
BenchmarkQuery/sql/prep-stmt/multiple-rows-12          	   78828	     75760 ns/op
BenchmarkQuery/sqlx/single-row-12                      	   41727	    141424 ns/op
BenchmarkQuery/sqlx/multiple-rows-12                   	   41360	    148159 ns/op
BenchmarkQuery/sqlx/prep-stmt/single-row-12            	   81553	     68347 ns/op
BenchmarkQuery/sqlx/prep-stmt/multiple-rows-12         	   77161	     77070 ns/op
BenchmarkQuery/pgxpool/single-row-12                   	   85140	     68628 ns/op
BenchmarkQuery/pgxpool/multiple-rows-12                	   76016	     73659 ns/op
BenchmarkQuery/gorm/single-row-12                      	   79791	     74779 ns/op
BenchmarkQuery/gorm/multiple-rows-12                   	   63621	     94351 ns/op
BenchmarkQuery/sqlc/single-row-12                      	   41904	    142480 ns/op
BenchmarkQuery/sqlc/multiple-rows-12                   	   39877	    147798 ns/op
BenchmarkQuery/sqlc/prep-stmt/single-row-12            	   84484	     68351 ns/op
BenchmarkQuery/sqlc/prep-stmt/multiple-rows-12         	   81837	     76040 ns/op
BenchmarkQuery/sqlboiler/single-row-12                 	   67383	     90907 ns/op
BenchmarkQuery/sqlboiler/multiple-rows-12              	   64791	     91555 ns/op
PASS
ok  	github.com/vingarcia/ksql/benchmarks	228.871s
Benchmark executed at: 2022-09-29
Benchmark executed on commit: fc2b32d91965404c2479aa3d1be904b5a4c217f4

Running the KSQL tests (for contributors)

The tests use docker-test for setting up all the supported databases, which means that:

• You need to have docker installed

• You must be able to run docker without sudo, i.e. if you are not root you should add yourself to the docker group, e.g.:

  $ sudo usermod <your_username> -aG docker
  

  And then restart your login session (or just reboot)

After that you can just run the tests by using:

make test

But it is recommended to first download the required images using:

docker pull postgres:14.0
docker pull mysql:8.0.27
docker pull mcr.microsoft.com/mssql/server:2017-latest

Otherwise the first attempt to run the tests will spend a long time downloading these images and then fail because the TestMain() function is configured to kill the containers after 20 seconds.

TODO List

• Add support for serializing structs as other formats such as YAML
• Update ksqltest.FillStructWith to work with ksql:"..,json" tagged attributes
• Create a way for users to submit user defined dialects
• Improve error messages (ongoing)
• Add support for the Patch function to work with maps for partial updates
• Add support for the Insert function to work with maps
• Add support for a ksql.Array(params ...interface{}) for allowing queries like this: db.Query(ctx, &user, "SELECT * FROM user WHERE id in (?)", ksql.Array(1,2,3))
• Improve docs about ksql.Mock

Optimization Oportunities

• Test if using a pointer on the field info is faster or not
• Consider passing the cached structInfo as argument for all the functions that use it, so that we don't need to get it more than once in the same call.
• Use a cache to store often used queries (like pgx)
• Preload the insert method for all dialects inside ksql.NewTable()
• Use prepared statements for the helper functions, Update, Insert and Delete.

Features for a possible V2

• Change the .Transaction(db ksql.Provider) to a .Transaction(ctx context.Context)
• Make the .Query() method to return a type Query interface { One(); All(); Chunks(); }
• Have an Update() method that updates without ignoring NULLs as Patch() does
• Rename NewTable() to just Table() so it feels right to declare it inline when convenient