b41sh/badger — explained in plain English
Analysis updated 2026-07-18 · repo last pushed 2020-01-13
Add fast local key-value storage to a Go application without running a separate database server.
Build a caching layer or logging system backed by crash-safe on-disk persistence.
Use it as the storage engine for a larger system, the way Dgraph uses it at scale.
| b41sh/badger | 0verflowme/alarm-clock | 0verflowme/seclists | |
|---|---|---|---|
| Language | — | CSS | — |
| Last pushed | 2020-01-13 | 2022-10-03 | 2020-05-03 |
| Maintenance | Dormant | Dormant | Dormant |
| Setup difficulty | easy | easy | easy |
| Complexity | 3/5 | 2/5 | 1/5 |
| Audience | developer | vibe coder | ops devops |
Figures from each repo's GitHub metadata at analysis time.
No external dependencies beyond Go, just point it at a folder on disk to get started.
BadgerDB is a fast, built-in database that stores key-value pairs, think of it like a dictionary where you save information under a label and retrieve it quickly later. It's written in Go and designed to be embedded directly into your application, so you don't need to run a separate database server. The main appeal is speed and reliability. It works entirely in Go (no external dependencies except for optional compression), persists your data safely to disk so nothing is lost if your program crashes, and supports transactions so you can make multiple changes atomically, either all succeed or all fail. It handles concurrent access, meaning multiple parts of your code can read and write data at the same time without conflicts. The README notes it's stable enough to handle datasets worth hundreds of terabytes and runs nightly crash-test simulations to prove it. In practice, you'd use this if you're building an application that needs fast local storage, like a cache, a logging system, or a backend for a mobile app. You open the database by pointing it to a folder on disk, then use straightforward commands to save (Set), retrieve (Get), and delete (Delete) data. It also supports advanced features like automatic expiration of old data (TTL), merging operations to combine values, and ways to efficiently scan through all your stored keys. The project is the underlying storage engine for Dgraph, a distributed graph database, which shows it's proven at scale. One notable design choice: rather than following traditional semantic versioning, the project only changes its major version number when the disk format changes incompatibly. This makes clear what you can safely upgrade to without migrating your data. The README recommends using the simpler DB.View() and DB.Update() methods for transactions rather than manually managing them, which keeps code cleaner and safer from bugs.
A fast embedded key-value database written in Go that stores data directly inside your application, with transactions and crash-safe disk persistence.
Dormant — no commits in 2+ years (last push 2020-01-13).
Setup difficulty is rated easy, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
double-check against the repo, no cap.