Bun is brought to you by ⭐ uptrace/uptrace. Uptrace is an open source and blazingly fast distributed tracing tool powered by OpenTelemetry and ClickHouse. Give it a star as well!
- Works with PostgreSQL, MySQL (including MariaDB), MSSQL, SQLite.
- ORM-like experience using good old SQL. Bun supports structs, map, scalars, and slices of map/structs/scalars.
- Bulk inserts.
- Bulk updates using common table expressions.
- Bulk deletes.
- Fixtures.
- Migrations.
- Soft deletes.
Resources:
Featured projects using Bun:
- uptrace - Distributed tracing and metrics.
- paralus - All-in-one Kubernetes access manager.
- inovex/scrumlr.io - Webapp for collaborative online retrospectives.
- gotosocial - Golang fediverse server.
- lorawan-stack - The Things Stack, an Open Source LoRaWAN Network Server.
- anti-phishing-bot - Discord bot for deleting Steam/Discord phishing links.
- emerald-web3-gateway - Web3 Gateway for the Oasis Emerald paratime.
- lndhub.go - accounting wrapper for the Lightning Network.
- penguin-statistics - Penguin Statistics v3 Backend.
- And hundreds more.
So you can elegantly write complex queries:
regionalSales := db.NewSelect().
ColumnExpr("region").
ColumnExpr("SUM(amount) AS total_sales").
TableExpr("orders").
GroupExpr("region")
topRegions := db.NewSelect().
ColumnExpr("region").
TableExpr("regional_sales").
Where("total_sales > (SELECT SUM(total_sales) / 10 FROM regional_sales)")
var items []map[string]interface{}
err := db.NewSelect().
With("regional_sales", regionalSales).
With("top_regions", topRegions).
ColumnExpr("region").
ColumnExpr("product").
ColumnExpr("SUM(quantity) AS product_units").
ColumnExpr("SUM(amount) AS product_sales").
TableExpr("orders").
Where("region IN (SELECT region FROM top_regions)").
GroupExpr("region").
GroupExpr("product").
Scan(ctx, &items)
WITH regional_sales AS (
SELECT region, SUM(amount) AS total_sales
FROM orders
GROUP BY region
), top_regions AS (
SELECT region
FROM regional_sales
WHERE total_sales > (SELECT SUM(total_sales)/10 FROM regional_sales)
)
SELECT region,
product,
SUM(quantity) AS product_units,
SUM(amount) AS product_sales
FROM orders
WHERE region IN (SELECT region FROM top_regions)
GROUP BY region, product
And scan results into scalars, structs, maps, slices of structs/maps/scalars:
users := make([]User, 0)
if err := db.NewSelect().Model(&users).OrderExpr("id ASC").Scan(ctx); err != nil {
panic(err)
}
user1 := new(User)
if err := db.NewSelect().Model(user1).Where("id = ?", 1).Scan(ctx); err != nil {
panic(err)
}
See Getting started guide and check examples.
Thanks to all the people who already contributed!