# NutsDB — Fast Embeddable Key-Value Store in Pure Go

> A simple, fast, embeddable, and persistent key/value store written in pure Go with support for lists, sets, sorted sets, and fully serializable transactions.

## Install

Save in your project root:

# NutsDB — Fast Embeddable Key-Value Store in Pure Go

## Quick Use
```go
import "github.com/nutsdb/nutsdb"

db, _ := nutsdb.Open(nutsdb.DefaultOptions,
    nutsdb.WithDir("/tmp/nutsdb"))
defer db.Close()

db.Update(func(tx *nutsdb.Tx) error {
    return tx.Put("bucket1", []byte("key"), []byte("value"), 0)
})
```

## Introduction
NutsDB is an embeddable, persistent key/value store written in pure Go. It supports multiple data structures including strings, lists, sets, and sorted sets, all within a single-file database with ACID transaction guarantees. It is designed for applications that need a fast embedded database without running a separate server process.

## What NutsDB Does
- Stores key/value pairs with optional TTL expiration
- Supports list, set, and sorted set data structures within buckets
- Provides fully serializable ACID transactions
- Persists data using an append-only log with automatic compaction
- Offers prefix and range scan operations for ordered iteration

## Architecture Overview
NutsDB uses a bitcask-inspired append-only write model combined with an in-memory index (B+ tree or hash map) for fast lookups. All writes go to a write-ahead entry log on disk, while the in-memory index maps keys to their on-disk positions. Background merge processes compact old log segments to reclaim space. Transactions use a copy-on-write approach with commit-time conflict detection.

## Self-Hosting & Configuration
- Import as a Go module: go get github.com/nutsdb/nutsdb
- Open a database by specifying a data directory path
- Configure segment size, sync strategy, and index type via options
- Choose between B+ tree index (range scans) or hash map index (point lookups)
- Set entry-level TTL for automatic expiration of stale data

## Key Features
- Pure Go implementation with zero CGo dependencies
- Multiple data structures (KV, list, set, sorted set) in a unified API
- B+ tree index mode enabling efficient prefix and range scans
- Configurable TTL per entry for cache-like expiration behavior
- Automatic log segment merging for space reclamation

## Comparison with Similar Tools
- **BoltDB/bbolt** — B+ tree with page-level MVCC; NutsDB uses a bitcask log with richer data structures (lists, sets)
- **BadgerDB** — LSM-tree optimized for SSDs; NutsDB uses an append-only log with simpler compaction
- **LevelDB/RocksDB** — C/C++ engines; NutsDB is pure Go with no CGo overhead
- **Redis** — in-memory server with similar data structures; NutsDB is an embedded library with disk persistence

## FAQ
**Q: Does NutsDB support concurrent access?**
A: Yes, NutsDB supports concurrent reads and serialized writes within a single process using its transaction system.

**Q: How does TTL work?**
A: Each entry can be stored with a TTL in seconds. Expired entries are cleaned up during reads and background merge operations.

**Q: What index modes are available?**
A: NutsDB offers B+ tree index mode for range scans and prefix queries, and hash map index mode for faster point lookups.

**Q: Is NutsDB suitable for production use?**
A: NutsDB is used in production by several projects. It works well for embedded storage scenarios where a separate database server is not desired.

## Sources
- https://github.com/nutsdb/nutsdb
- https://nutsdb.github.io/nutsdb/

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Source: https://tokrepo.com/en/workflows/asset-5180acdf
Author: AI Open Source