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RocksDB vs TokuMX: What are the differences?
Developers describe RocksDB as "Embeddable persistent key-value store for fast storage, developed and maintained by Facebook Database Engineering Team". RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation. On the other hand, TokuMX is detailed as "A high-performance, concurrent, compressing, drop-in replacement engine for MongoDB". TokuMX is a drop-in replacement for MongoDB, and offers 20X performance improvements, 90% reduction in database size, and support for ACID transactions with MVCC. TokuMX has the same binaries, supports the same drivers, data model, and features of MongoDB, because it shares much of its code with MongoDB.
RocksDB and TokuMX belong to "Databases" category of the tech stack.
"Very fast" is the primary reason why developers consider RocksDB over the competitors, whereas "When your two-week MongoDB love affair ends, try this" was stated as the key factor in picking TokuMX.
RocksDB and TokuMX are both open source tools. It seems that RocksDB with 14.3K GitHub stars and 3.12K forks on GitHub has more adoption than TokuMX with 679 GitHub stars and 90 GitHub forks.
I am researching different querying solutions to handle ~1 trillion records of data (in the realm of a petabyte). The data is mostly textual. I have identified a few options: Milvus, HBase, RocksDB, and Elasticsearch. I was wondering if there is a good way to compare the performance of these options (or if anyone has already done something like this). I want to be able to compare the speed of ingesting and querying textual data from these tools. Does anyone have information on this or know where I can find some? Thanks in advance!
You've probably come to a decision already but for those reading...here are some resources we put together to help people learn more about Milvus and other databases https://zilliz.com/comparison and https://github.com/zilliztech/VectorDBBench. I don't think they include RocksDB or HBase yet (you could could recommend on GitHub) but hopefully they help answer your Elastic Search questions.
Pros of RocksDB
- Very fast5
- Made by Facebook3
- Consistent performance2
- Ability to add logic to the database layer where needed1
Pros of TokuMX
- When your two-week MongoDB love affair ends, try this3