README.md

bitcask

A high performance Key/Value store written in Go with a predictable read/write performance and high throughput. Uses a Bitcask on-disk layout (LSM+WAL) similar to Riak

For a more feature-complete Redis-compatible server, distributed key/value store have a look at Bitraft which uses this library as its backend. Use Bitcask as a starting point or if you want to embed in your application, use Bitraft if you need a complete server/client solution with high availability with a Redis-compatible API.

Features

• Embedded (import "github.com/prologic/bitcask")
• Builtin CLI (bitcask)
• Builtin Redis-compatible server (bitcaskd)
• Predictable read/write performance
• Low latency
• High throughput (See: Performance )

Is Bitcask right for my project?

NOTE: Please read this carefully to identify whether using Bitcask is suitable for your needs.

bitcask is a great fit for:

• Storing hundreds of thousands to millions of key/value pairs based on default configuration. With the default configuration (configurable) of 64 bytes per key and 64kB values, 1M keys would consume roughly ~600-700MB of memory ~65-70GB of disk storage. These are all configurable when you create a new database with bitcask.Open(...) with functional-style options you can pass with WithXXX().

• As the backing store to a distributed key/value store. See for example the bitraft as an example of this.

• For high performance, low latency read/write workloads where you cannot fit a typical hash-map into memory, but require the highest level of performance and predicate read latency. Bitcask ensures only 1 read/write IOPS are ever required for reading and writing key/value pairs.

• As a general purpose embedded key/value store where you would have used BoltDB, LevelDB, BuntDB or similar...

bitcask is not suited for:

• Storing billions of records The reason for this is the key-space is held in memory using a highly performant and memory optimized adaptive radix tree thanks to go-adaptive-radix-tree however this means the more keys you have in your key space, the more memory is consumed. Consider using a disk-backed B-Tree like BoltDB or LevelDB if you intend to store a large quantity of key/value pairs.

Note however that storing large amounts of data in terms of value(s) is totally fine. In other wise thousands to millions of keys with large values will work just fine.

• Write intensive workloads. Due to the Bitcask design heavy write workloads that lots of key/value pairs will over time cause problems like "Too many open files" (#193) errors to occur. This can be mitigated by periodically compacting the data files by issuing a .Merge() operation however if key/value pairs do not change or are never deleted, as-in only new key/value pairs are ever written this will have no effect. Eventually you will run out of file descriptors!

You should consider your read/write workloads carefully and ensure you set appropriate file descriptor limits with ulimit -n that suit your needs.

Development

$ git clone https://github.com/prologic/bitcask.git
$ make

Install

$ go get github.com/prologic/bitcask

Usage (library)

Install the package into your project:

$ go get github.com/prologic/bitcask

package main

import (
	"log"
	"github.com/prologic/bitcask"
)

func main() {
    db, _ := bitcask.Open("/tmp/db")
    defer db.Close()
    db.Put([]byte("Hello"), []byte("World"))
    val, _ := db.Get([]byte("Hello"))
    log.Printf(string(val))
}

See the GoDoc for further documentation and other examples.

Usage (tool)

$ bitcask -p /tmp/db set Hello World
$ bitcask -p /tmp/db get Hello
World

Usage (server)

There is also a builtin very simple Redis-compatible server called bitcaskd:

$ ./bitcaskd ./tmp
INFO[0000] starting bitcaskd v0.0.7@146f777              bind=":6379" path=./tmp

Example session:

$ telnet localhost 6379
Trying ::1...
Connected to localhost.
Escape character is '^]'.
SET foo bar
+OK
GET foo
$3
bar
DEL foo
:1
GET foo
$-1
PING
+PONG
QUIT
+OK
Connection closed by foreign host.

Docker

You can also use the Bitcask Docker Image:

$ docker pull prologic/bitcask
$ docker run -d -p 6379:6379 prologic/bitcask

Performance

Benchmarks run on a 11" MacBook with a 1.4Ghz Intel Core i7:

$ make bench
...
goos: darwin
goarch: amd64
pkg: github.com/prologic/bitcask

BenchmarkGet/128B-4         	  316515	      3263 ns/op	  39.22 MB/s	     160 B/op	       1 allocs/op
BenchmarkGet/256B-4         	  382551	      3204 ns/op	  79.90 MB/s	     288 B/op	       1 allocs/op
BenchmarkGet/512B-4         	  357216	      3835 ns/op	 133.51 MB/s	     576 B/op	       1 allocs/op
BenchmarkGet/1K-4           	  274958	      4429 ns/op	 231.20 MB/s	    1152 B/op	       1 allocs/op
BenchmarkGet/2K-4           	  227764	      5013 ns/op	 408.55 MB/s	    2304 B/op	       1 allocs/op
BenchmarkGet/4K-4           	  187557	      5534 ns/op	 740.15 MB/s	    4864 B/op	       1 allocs/op
BenchmarkGet/8K-4           	  153546	      7652 ns/op	1070.56 MB/s	    9472 B/op	       1 allocs/op
BenchmarkGet/16K-4          	  115549	     10272 ns/op	1594.95 MB/s	   18432 B/op	       1 allocs/op
BenchmarkGet/32K-4          	   69592	     16405 ns/op	1997.39 MB/s	   40960 B/op	       1 allocs/op

BenchmarkPut/128BNoSync-4   	  123519	     11094 ns/op	  11.54 MB/s	      49 B/op	       2 allocs/op
BenchmarkPut/256BNoSync-4   	   84662	     13398 ns/op	  19.11 MB/s	      50 B/op	       2 allocs/op
BenchmarkPut/1KNoSync-4     	   46345	     24855 ns/op	  41.20 MB/s	      58 B/op	       2 allocs/op
BenchmarkPut/2KNoSync-4     	   28820	     43817 ns/op	  46.74 MB/s	      68 B/op	       2 allocs/op
BenchmarkPut/4KNoSync-4     	   13976	     90059 ns/op	  45.48 MB/s	      89 B/op	       2 allocs/op
BenchmarkPut/8KNoSync-4     	    7852	    155101 ns/op	  52.82 MB/s	     130 B/op	       2 allocs/op
BenchmarkPut/16KNoSync-4    	    4848	    238113 ns/op	  68.81 MB/s	     226 B/op	       2 allocs/op
BenchmarkPut/32KNoSync-4    	    2564	    391483 ns/op	  83.70 MB/s	     377 B/op	       3 allocs/op

BenchmarkPut/128BSync-4     	     260	   4611273 ns/op	   0.03 MB/s	      48 B/op	       2 allocs/op
BenchmarkPut/256BSync-4     	     265	   4665506 ns/op	   0.05 MB/s	      48 B/op	       2 allocs/op
BenchmarkPut/1KSync-4       	     256	   4757334 ns/op	   0.22 MB/s	      48 B/op	       2 allocs/op
BenchmarkPut/2KSync-4       	     255	   4996788 ns/op	   0.41 MB/s	      92 B/op	       2 allocs/op
BenchmarkPut/4KSync-4       	     222	   5136481 ns/op	   0.80 MB/s	      98 B/op	       2 allocs/op
BenchmarkPut/8KSync-4       	     223	   5530824 ns/op	   1.48 MB/s	      99 B/op	       2 allocs/op
BenchmarkPut/16KSync-4      	     213	   5717880 ns/op	   2.87 MB/s	     202 B/op	       2 allocs/op
BenchmarkPut/32KSync-4      	     211	   5835948 ns/op	   5.61 MB/s	     355 B/op	       3 allocs/op

BenchmarkScan-4             	  568696	      2036 ns/op	     392 B/op	      33 allocs/op
PASS

For 128B values:

• ~300,000 reads/sec
• ~90,000 writes/sec
• ~490,000 scans/sec

The full benchmark above shows linear performance as you increase key/value sizes.

Support

Support the ongoing development of Bitcask!

Sponsor

• Become a Sponsor

Stargazers over time

Contributors

Thank you to all those that have contributed to this project, battle-tested it, used it in their own projects or products, fixed bugs, improved performance and even fix tiny typos in documentation! Thank you and keep contributing!

You can find an AUTHORS file where we keep a list of contributors to the project. If you contribute a PR please consider adding your name there. There is also GitHub's own Contributors statistics.

Related Projects

• bitraft -- A Distributed Key/Value store (using Raft) with a Redis compatible protocol.
• bitcaskfs -- A FUSE file system for mounting a Bitcask database.
• bitcask-bench -- A benchmarking tool comparing Bitcask and several other Go key/value libraries.

License

bitcask is licensed under the term of the MIT License