Disk-based Redis implementation
Project description
DRedis: Disk-based Redis implementation
Redis is a great key-value database and it's extremely fast because it's in-memory. Some people want Redis's rich data types without having to worry about the memory limitations. For those that can afford slower performance and want unlimited storage, DRedis may be an alternative.
WARNING: This project is still experimental and it doesn't implement all Redis commands!
Installing
Make sure to install the LevelDB C++ library (apt-get install libleveldb-dev
or brew install leveldb
) and then run:
$ pip install dredis
Running
$ dredis --dir /tmp/dredis-data
To know about all of the options, use --help
:
$ dredis --help
usage: dredis [-h] [-v] [--host HOST] [--port PORT] [--dir DIR] [--debug]
[--flushall]
optional arguments:
-h, --help show this help message and exit
-v, --version show program's version number and exit
--host HOST server host (defaults to 127.0.0.1)
--port PORT server port (defaults to 6377)
--dir DIR directory to save data (defaults to a temporary directory)
--debug enable debug logs
--flushall run FLUSHALL on startup
If you want to try it with docker locally (port 6377 on the host):
$ docker-compose up
Supported Commands
Command signature | Type |
---|---|
COMMAND* | Server |
FLUSHALL | Server |
FLUSHDB | Server |
DBSIZE | Server |
DEL key [key ...] | Keys |
TYPE key | Keys |
KEYS pattern | Keys |
EXISTS key [key ...] | Keys |
PING [msg] | Connection |
SELECT db | Connection |
SET key value | Strings |
GET key | Strings |
INCR key | Strings |
INCRBY key increment | Strings |
GETRANGE key start end | Strings |
SADD key value [value ..] | Sets |
SMEMBERS key | Sets |
SCARD key | Sets |
SISMEMBER key value | Sets |
EVAL script numkeys [key ...] [arg ...] | Scripting |
ZADD key score member [score member ...] | Sorted Sets |
ZRANGE key start top [WITHSCORES] | Sorted Sets |
ZCARD key | Sorted Sets |
ZREM key member [member ...] | Sorted Sets |
ZSCORE key member | Sorted Sets |
ZRANK key member | Sorted Sets |
ZCOUNT key min_score max_score | Sorted Sets |
ZRANGEBYSCORE key min_score max_score [WITHSCORES] [LIMIT offset count] | Sorted Sets |
ZUNIONSTORE destination numkeys key [key ...] [WEIGHTS weight [weight ...]] | Sorted Sets |
HSET key field value [field value ...] | Hashes |
HDEL key field [field ...] | Hashes |
HSETNX key field value | Hashes |
HGET key value | Hashes |
HKEYS key | Hashes |
HVALS value | Hashes |
HLEN key | Hashes |
HINCRBY key field increment | Hashes |
HGETALL key | Hashes |
* COMMAND
's reply is incompatible at the moment, it returns a flat array with command names (their arity, flags, positions, or step count are not returned).
How is DRedis implemented
Initially DRedis had its own filesystem structure, but then it was converted to use LevelDB, which is a lot more reliable and faster. Other projects implement similar features to what's available on DRedis, but they aren't what Yipit needed when the project started. Some similar projects follow:
- https://github.com/Qihoo360/pika
- https://github.com/KernelMaker/blackwidow
- https://github.com/siddontang/ledisdb
- https://github.com/reborndb/qdb
- https://github.com/alash3al/redix
- https://github.com/meitu/titan
Lua support
Lua is supported through the lupa library.
Challenges
Data Consistency
We are relying on LevelDB's consistency, no stress tests were performed.
Cluster mode & Replication
Replication, key distribution, and cluster mode isn't supported. If you want higher availability you can create multiple servers that share or replicate a disk (consistency may suffer when replicating). Use DNS routing or a network load balancer to route requests properly.
Backups
There are many solutions to back up files. DRedis will have no impact when backups are performed because it's done from the outside (different from Redis, which uses fork()
to snapshot the data).
A straightforward approach is to have period backups to an object storage such as Amazon S3.
The commands SAVE or BGSAVE will be supported in the future to guarantee consistency when generating backups.
This project includes a snapshot utility (dredis-snapshot
) to make it easier to back up data locally or to AWS S3.
Be aware that there may be consistency issues during the snapshot (dredis
won't pause during the temporary copy of the data directory).
Why Python
Because it's a good language to get things off the ground quickly and @hltbra knows it very well. If this becomes a valuable project, other languages will be evaluated — the language of choice won't affect much of the I/O bottleneck, though.
Python 3 will be eventually supported, @hltbra didn't want to deal with bytes/str shenanigans when this project started as a proof-of-concept.
Didn't you have better names?
@andrewgross suggested REDISK. The name will only matter if this project survives, it's still an experiment. Also, other projects use the name redisk.
@nadlerjessie is okay with the name dredis but wants it to be pronunced "Doctor Redis". The YipitData engineering team has fun with this pronunciation.
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