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RethinkDB vs RocksDB: What are the differences?
What is RethinkDB? JSON. Scales to multiple machines with very little effort. Open source. RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.
What is RocksDB? 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.
RethinkDB and RocksDB can be categorized as "Databases" tools.
Some of the features offered by RethinkDB are:
- JSON data model and immediate consistency.
- Distributed joins, subqueries, aggregation, atomic updates.
- Secondary, compound, and arbitrarily computed indexes.
On the other hand, RocksDB provides the following key features:
- Designed for application servers wanting to store up to a few terabytes of data on locally attached Flash drives or in RAM
- Optimized for storing small to medium size key-values on fast storage -- flash devices or in-memory
- Scales linearly with number of CPUs so that it works well on ARM processors
"Powerful query language" is the top reason why over 46 developers like RethinkDB, while over 2 developers mention "Very fast" as the leading cause for choosing RocksDB.
RethinkDB and RocksDB are both open source tools. It seems that RethinkDB with 22.4K GitHub stars and 1.74K forks on GitHub has more adoption than RocksDB with 14.3K GitHub stars and 3.12K GitHub forks.
According to the StackShare community, RethinkDB has a broader approval, being mentioned in 37 company stacks & 25 developers stacks; compared to RocksDB, which is listed in 6 company stacks and 7 developer stacks.
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.
I’m newbie I was developing a pouchdb and couchdb app cause if the sync. Lots of learning very little code available. I dropped the project cause it consumed my life. Yeats later I’m back into it. I researched other db and came across rethinkdb and mongo for the subscription features. With socketio I should be able to create and similar sync feature. Attempted to use mongo. I attempted to use rethink. Rethink for the win. Super clear l. I had it running in minutes on my local machine and I believe it’s supposed to scale easy. Mongo wasn’t as easy and there free online db is so slow what’s the point. Very easy to find mongo code examples and use rethink code in its place. I wish I went this route years ago. All that corporate google Amazon crap get bent. The reason they have so much power in the world is cause you guys are giving it to them.
Pros of RethinkDB
- Powerful query language48
- Excellent dashboard46
- JSON42
- Distributed database41
- Open source38
- Reactive25
- Atomic updates16
- Joins15
- MVCC concurrency9
- Hadoop-style map/reduce9
- Geospatial support4
- Real-time, open-source, scalable4
- YC Company2
- A NoSQL DB with joins2
- Great Admin UI2
- Changefeeds: no polling needed to get updates2
- Fast, easily scalable, great customer support2
Pros of RocksDB
- Very fast5
- Made by Facebook3
- Consistent performance2
- Ability to add logic to the database layer where needed1
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