RocksDB优势：

rocksdb相对于innodb提供的API层次性更好，意味着基于rockdb开发的数据后端通用性，移植性会更好，这也是spdk目前暂时仅支持rocksdb的原因之一。性能方面之前已经有过不少的相关的对比测试，如根据 http://smalldatum.blogspot.com/2016/01/rocksdb-vs-innodb-via-linkbench.html 的测试结果，其指出rocksdb相较于innodb压缩占用空间更少，同时针对磁盘的写次数更少，盘相应时间也更少。

- Uncompressed InnoDB loads faster than MyRocks and MyRocks loads faster than compressed InnoDB. I hope to figure out how to make MyRocks load faster than uncompressed InnoDB.

- MyRocks uses about half the disk space compared to compressed InnoDB.

- MyRocks writes much less to storage than InnoDB. This allows a workload to run on low-endurance SSD with MyRocks when it requires high-endurance SSD with InnoDB.

- Average and p99 response times are much better for MyRocks

- Maximum response times were usually better for InnoDB

RocksDB劣势：

不支持以下特性：

- 隔离仅支持RR，RC。对应可能的问题如下表：

作为MySQL的默认引擎，其支持xa，savepoint，这些rocksdb是不支持

以下列出的限制摘录于 https://www.percona.com/doc/percona-server/LATEST/myrocks/limitations.html

Online DDL

ALTER TABLE ... EXCHANGE PARTITION

SAVEPOINT

Transportable tablespace

当前RocksDB状态

wiki上比较清晰的梳理了当前使用rocksdb作为可选数据引擎（Alternative backend）或已内置rocksdb（Embedded）的数据库管理系统。可以看到MySQL可以用MyRocks（基于rocksdb开发）作为可选的数据引擎，Ceph的bluestore直接用了rocksdb来作为OSD节点上metadata的管理。

Alternative backend

The following projects have been started to replace or offer an alternative storage engines for already-established database systems with RocksDB:

MongoDB

The MongoRocks project provides a storage module for MongoDB where the storage engine is RocksDB.

A related program is Rocks Strata, a tool written in Go , which allows managing incremental backups of MongoDB when RocksDB is used as the storage engine.

MySQL

The MyRocks project creates a new RocksDB based storage engine for MySQL .In-depth details about MyRocks were presented at Percona Live 2016.

Cassandra

Cassandra on RocksDB can improve the performance of Apache Cassandra significantly (3-4 times faster in general, 100 times faster in some use-cases. "Cassandra on RocksDB at Percona Live 2018" .) The Instagram team at Facebook developed and open-sourced their code, along with benchmarks of their performance results. "Open-sourcing a 10x reduction in Apache Cassandra tail latency" .