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I like that RethinkDB is open source, fast and declarative. It has a wonderful built in visualization tooling and works across many different server types. Review collected by and hosted on G2.com.
It is a new tech and has limited documentation, as well as very few people using it in production environments. Review collected by and hosted on G2.com.
14 out of 15 Total Reviews for RethinkDB
Overall Review Sentiment for RethinkDB
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ReQL, RethinkDB's query language is one of my absolute favourite things it offers. As someone who isn't very fond of generic SQL databases, ReQL feels just like programming, and I don't have to shift mind-sets to think about another language. Review collected by and hosted on G2.com.
Unfortunately, RethinkDB is no longer actively developed, and was the company behind RethinkDB officially shut down in October 2016. The project has since joined The Linux Foundation and has seen one update in mid-2017, but the future for RethinkDB isn't looking too positive currently. Review collected by and hosted on G2.com.
First what I like best is the transparency of the RethinkDB team and its dedication to make RethinkDB a user-friendly product.
The website is full of information about the current bugs and performance issues. And there is a real effort to make the product very user-friendly: a nice documentation, a beautiful UI, a clean and well-thought API, simple sharding and replication features, joins, real-time features...
It really has lots of attractive features for such a young product. Review collected by and hosted on G2.com.
RethinkDB is still quite slow for many operations. I know a Swiss start-up that switched from RethinkDB to PostgreSQL because of performance issues. These problems could be fixed in the future but if you need good performance right now at the very least do some benchmark and load-testing before investing too much in this database.
Also using RethinkDB made me realize that I prefer databases that use a text-based query language (SQL databases, Cassandra, Redis, ...) than databases that use a Javascript API by default (MongoDB, RethinkDB, ...) because:
- drivers in other languages are easier to implement when you just have to send some tex queriest than when you have to mimic the Javascript API.
- Javascript is a very dynamic language and it is sometimes hard to mimic the Javascript API in other languages, especially in compiled ones. It makes the API in all languages different, so you first have to learn the Javascript API and then you have to look how to do it in your language. The languages in the official documentation are JavaScript, Python, Ruby and Java. So be careful if you are not using one of these languages.
- It makes unit tests more difficult to do. A database with a large API containing plenty of functions is harder to mock than a SQL database with a leaner API. Review collected by and hosted on G2.com.
There a ton of things to like about RethinkDB. Of particular interest are the query language which feels just like programming. I'm a big fan of the community around it because they've very welcoming and supportive as well. It's well designed and everything is done out in the open which builds a lot of trust and understanding. Review collected by and hosted on G2.com.
One downside is that using the in-browser data explorer requires you to write your queries in JavaScript. I do most of my analysis in Python so the conversion can be a pain sometimes. It'd be nice to be able to write Python in the browser but I understand the challenges of making that a reality. Review collected by and hosted on G2.com.
I LOVE the automatic replication and sharding features in RethinkDB. It's so incredibly simple, and the web UI does a fantastic job of letting you know what's happening with your cluster. The realtime updates make everything feel very refined.
I also enjoy how easy it is to interact with RethinkDB from a variety of tools. I've used RethinkDB primarily with Python, but I've also dabbled with some of the other drivers. The fairly consistent interface is very helpful. Review collected by and hosted on G2.com.
The last time I paid attention, RethinkDB used significantly more disk space than some other solutions that I evaluated at the same time with the same dataset. This was several years ago now. Disk consumption is a lot better now, but it's still more than I would prefer.
Data ingestion speed wasn't quite what I had hoped when I benchmarked it recently. This was in a small-scale test environment, though, and I'm sure a proper environment would perform much better. Review collected by and hosted on G2.com.
My favourite features of RethinkDB are the team behind it, the real time features, and the query language.
The RethinkDB team are the nicest group I have ever worked with in open source. They are patient, responsive, kind, and friendly. When reporting bugs and writing patches they are great to work with.
The real time queries are a breakthrough, and make writing real-time apps much easier than before.
I also really like the query language. It is a functional query language which works well with the functional programming language we are using to talk to RethinkDB (Clojure). Review collected by and hosted on G2.com.
I don't really have any dislikes of RethinkDB. It is a document database, so you don't have SQL features like multi document transactions and schemas, but you would get that with any database. Review collected by and hosted on G2.com.
Rethink is an easy to setup and easy to use NoSQL database that I started to use for a project in my work. The main feature that made use choose Rethink instead of other well known NoSQL database was the change feed that was crucial for the project goal.
I found that the installation and usage of RethinkDb was extremely easy to a beginner with no experience in NoSQL databases. And even with a standard installation we begun doing some really intensive work and Rethink was able to handle the load extremely well. Review collected by and hosted on G2.com.
I disliked that to use the database I had to manually create a connection inside a Python terminal. The lack of a more easy interaction with the data in the web admin. The only option is to interact with the data using Javascript which me being a Python developer is not really easy. So I'm forced to do any data manipulation through a Python terminal.
But that being said, that manipulation is really more easy than with SQL database. Review collected by and hosted on G2.com.
Real time updates using changes() syntax. We can use this feature to do most of the real time processing with less latency possible. Review collected by and hosted on G2.com.
It requires like minimum 2GB to run and i have seen some issue of memory leak too. Although its still evolving so we can expect these for now. Review collected by and hosted on G2.com.
The query language is amazing compared to other NoSQL query languages. I have only used MongoDB and Redis and compared to MongoDB, the query language is absolutely superb. Review collected by and hosted on G2.com.
The fact that it lacks atomic updates across multiple documents. This is the sole reason why we have switched to Postgres: Our data model became so much simpler once we could rely on transparent transactions. Review collected by and hosted on G2.com.
The way you get to query the database. It is absolutely brilliant. Being a fan of functional programming, it had been a god send to me. And then there is the real time change facilities although I dont use that much. Review collected by and hosted on G2.com.
Performance. The insertion, especially the batch insertion performance is rather slow. Also foubd it to be slower in geo queries compared to Mongo or Postgres with the same data. Review collected by and hosted on G2.com.
