A simple key/value store written in pure Go named NutsDB. It supports transactions and many data structures.

[xujiajun]

Hi, guys. i share you a key/value store named NutsDB.

NutsDB is a simple, fast, embeddable and persistent key/value store written in pure Go.

It supports fully serializable transactions and many data structures such as list、set、sorted set. All operations happen inside a Tx. Tx represents a transaction, which can be read-only or read-write. Read-only transactions can read values for a given bucket and given key or iterate over a set of key-value pairs. Read-write transactions can update and delete keys from the DB.

This project is still in the experimental stage and has not passed the test of the actual production environment. Welcome to issue and contribute

see repository link: https://github.com/xujiajun/nutsdb for detail.

 

Motivation

I wanted a simple, fast, embeddable and persistent key/value store written in pure Go. And if it supports more data structures such as list, set, sorted set，it will be better.

There are some options around the embeddable kv store in Go:

1. BoltDB,it is based on B+ tree, has a good random read performance and awesome sequential scan performance, and it supports ACID transactions with serializable isolation, but it is terrible at random write performance and not supports more data structures such as list etc.

2. GoLevelDB is based on a log-structured merge-tree (LSM tree), but it not supports transactions and more data structures.

3. Badger is based on LSM tree with value log. It designed for SSDs. It also supports transactions. But its write performance is not as good as i thought.And it also not supports more data structures.

So i tried to build a kv store by myself, i wanted to find a simple store engine model as reference. Finally i found the bitcask model. It is simple and easy to implement. Howerver it has its limition,like range or prefix queries are not effcient. For example, you can not easily scan over all keys between user000000 and user999999, you had to look up each key individully in the hashmap.

In order to break the limition, i tried to optimize them. Finally i did it and named NutsDB. 

 And it still has a lot of room for optimization. Welcome contributions to NutsDB. 

[Robert Engels]

There is also github.com/robaho/keydb which uses LSM and transactions and it is very fast :)

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