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Document-oriented, embedded SQL database, works with Bolt, Badger and memory
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README.md

Genji

Genji

Document-oriented, embedded, SQL database

Table of contents

Introduction

Build Status go.dev reference Slack channel

Genji is a schemaless database that allows running SQL queries on documents.

Checkout the SQL documentation, the Go doc and the usage example in the README to get started quickly.

⚠️ Genji's API is still unstable: Database compatibility is not guaranteed before reaching v1.0.0

Features

  • Optional schemas: Genji tables are schemaless, but it is possible to add constraints on any field to ensure the coherence of data within a table.
  • Multiple Storage Engines: It is possible to store data on disk or in ram, but also to choose between B-Trees and LSM trees. Genji relies on BoltDB and Badger to manage data.
  • Transaction support: Read-only and read/write transactions are supported by default.
  • SQL and Documents: Genji mixes the best of both worlds by combining powerful SQL commands with JSON dot notation.
  • Easy to use, easy to learn: Genji was designed for simplicity in mind. It is really easy to insert and read documents of any shape.
  • Compatible with the database/sql package

Installation

Install the Genji database

go get github.com/asdine/genji

Usage

There are two ways of using Genji, either by using Genji's API or by using the database/sql package.

Using Genji's API

// Create a database instance, here we'll store everything on-disk using the BoltDB engine
db, err := genji.Open("my.db")
if err != nil {
    log.Fatal(err)
}
// Don't forget to close the database when you're done
defer db.Close()

// Create a table. Genji tables are schemaless, you don't need to specify a schema if not needed.
err = db.Exec("CREATE TABLE user")

// Create an index.
err = db.Exec("CREATE INDEX idx_user_name ON test (name)")

// Insert some data
err = db.Exec("INSERT INTO user (id, name, age) VALUES (?, ?, ?)", 10, "Foo1", 15)

// Supported values can go from simple integers to richer data types like lists or documents
err = db.Exec(`
    INSERT INTO user (id, name, age, address, friends)
    VALUES (
        11,
        'Foo2',
        20,
        {"city": "Lyon", "zipcode": "69001"},
        ["foo", "bar", "baz"]
    )`)

// It is also possible to insert values using document notation, which is a JSON-like notation with support for expressions.
err = db.Exec(`
    INSERT INTO user
    VALUES {
        id: 11,
        name: 'Foo2',
        "age": 20,
        "address": {"city": "Lyon", "zipcode": "69001"},
        "friends": ["foo", "bar", "baz"],
        single: 1 AND 1
    }`)

// Or even to use structures
type User struct {
    ID              uint
    Name            []byte
    TheAgeOfTheUser float64 `genji:"age"`
    Address         struct {
        City    string
        ZipCode string
    }
}

// Let's create a user
u := User{
    ID: 20,
    Name: "foo",
    TheAgeOfTheUser: 40,
}
u.Address.City = "Lyon"
u.Address.ZipCode = "69001"

err := db.Exec(`INSERT INTO user VALUES ?`, &u)

// Use a transaction
tx, err := db.Begin(true)
defer tx.Rollback()
err = tx.Exec("INSERT INTO user (id, name, age) VALUES (?, ?, ?)", 12, "Foo3", 25)
...
err = tx.Commit()

// Query some documents
res, err := db.Query("SELECT id, name, age, address FROM user WHERE age >= ?", 18)
// always close the result when you're done with it
defer res.Close()

// Iterate over the results
err = res.Iterate(func(d document.Document) error {
    // When querying an explicit list of fields, you can use the Scan function to scan them
    // in order. Note that the types don't have to match exactly the types stored in the table
    // as long as they are compatible.
    var id int
    var name string
    var age int32
    var address struct{
        City string
        ZipCode string
    }

    err = document.Scan(d, &id, &name, &age, &address)
    if err != nil {
        return err
    }

    fmt.Println(id, name, age, address)

    // It is also possible to scan the results into a structure
    var u User
    err = document.StructScan(d, &user)
    if err != nil {
        return err
    }

    fmt.Println(u)

    // Or scan into a map
    var m map[string]interface{}
    err = document.MapScan(d, &m)
    if err != nil {
        return err
    }

    fmt.Println(m)
    return nil
})

// Count results
count, err := res.Count()

// Get first document from the results using the First method of the stream
d, err := res.First()

// Apply some transformations
err = res.
    // Filter all even ids
    Filter(func(d document.Document) (bool, error) {
        f, err := d.GetByField("id")
        ...
        id, err := f.DecodeToInt()
        ...
        return id % 2 == 0, nil
    }).
    // Enrich the documents with a new field
    Map(func(d document.Document) (document.Document, error) {
        var fb document.FieldBuffer

        err := fb.ScanDocument(r)
        ...
        fb.Add(document.NewTextValue("group", "admin"))
        return &fb, nil
    }).
    // Iterate on them
    Iterate(func(d document.Document) error {
        ...
    })

Using database/sql

// import Genji as a blank import
import _ "github.com/asdine/genji/sql/driver"

// Create a sql/database DB instance
db, err := sql.Open("genji", "my.db")
if err != nil {
    log.Fatal(err)
}
defer db.Close()

// Then use db as usual
res, err := db.ExecContext(...)
res, err := db.Query(...)
res, err := db.QueryRow(...)

Engines

Genji currently supports storing data in BoltDB, Badger and in-memory.

Use the BoltDB engine

import (
    "log"

    "github.com/asdine/genji"
)

func main() {
    db, err := genji.Open("my.db")
    defer db.Close()
}

Use the memory engine

import (
    "log"

    "github.com/asdine/genji"
)

func main() {
    db, err := genji.Open(":memory:")
    if err != nil {
        log.Fatal(err)
    }
    defer db.Close()
}

Use the Badger engine

The Badger engine must be installed first

go get github.com/asdine/genji/engine/badgerengine

Then, it can be instantiated using the genji.New function:

import (
    "log"

    "github.com/asdine/genji"
    "github.com/asdine/genji/engine/badgerengine"
    "github.com/dgraph-io/badger"
)

func main() {
    // Create a badger engine
    ng, err := badgerengine.NewEngine(badger.DefaultOptions("mydb")))
    if err != nil {
        log.Fatal(err)
    }

    // Pass it to genji
    db, err := genji.New(ng)
    if err != nil {
        log.Fatal(err)
    }
    defer db.Close()
}

Genji shell

The genji command line provides an SQL shell that can be used to create, modify and consult Genji databases.

Make sure the Genji command line is installed:

go get github.com/asdine/genji/cmd/genji

Example:

# Opening an in-memory database:
genji

# Opening a BoltDB database:
genji my.db

# Opening a Badger database:
genji --badger pathToData

Contributing

Contributions are welcome!

  • Feedback
  • Feature ideas
  • Bug reports
  • Pull Requests
  • Anything that comes to mind to improve Genji!

If you have any doubt, join the Gophers Slack channel or open an issue.

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