RethinkDB VS Apache Cassandra

I've been poking around, testing and breaking database servers for a long time (more than 20 years today). But a few years ago I came across a jewel, the grail, one of the best solutions available. Under the radar, shunned for whatever reason, RethinkDB is nonetheless one of the finest database server projects I've ever tested.

RethinkDB[0] looks like a "too good to be true" type of database. Anyone using it in production? What is your experience like? What are the pros and cons?

[0] https://rethinkdb.com

Since you’re not new to the field you might want to peek https://rethinkdb.com/ since it got picked up as an open source project.

No I don't think that's relevant. They implement their own btree it seems [0].

They don't use a key-value store library.

I know it's a bit of a fine line. But I'm talking about standalone libraries people embed across different applications/databases. That's what RocksDB/LevelDB/Pebble are.

[0] https://github.com/rethinkdb/rethinkdb/tree/v2.4.x/src/btree

A Data Objects represents data which can be saved inside a database. This concept is in the heart of SQLAlchemy, but as the name should be obvious: it's for SQL Database (in general). Today, there are now document databases too (like MongoDB, ArangoDB, RethinkDB that I love so much, or even PostgreSQL). So, a "data" is like a "structured and typed document" that you save "as is". That's not the same paradigm, not the same controls. There are advantages and disadvantages, but we won't debate that here.

There are multiple ways to share data between two (or more) instances of your app: - you can use a shared storage, such as Cloud Firestore, - you can build your own backend (based on a real-time database, such as RethinkDB), - or you can rely on local communication using the Multipeer framework you linked.

Apache Cassandra{:target="_blank"} is a highly scalable and fault-tolerant database that can handle large volumes of data across multiple nodes or clusters. It provides fast read and write operations, making it suitable for real-time analytics or applications with high throughput requirements.

Wide Column: Apache Cassandra, ScyllaDB and DynamoDB

Cassandra, a replicated, fault-tolerant, decentralized and scalable database system.

A popular database you might already be familiar with is Apache Cassandra®, which powers high-performing applications for thousands of companies including Hulu, Netflix, Spotify, and Apple. While this free, open-source database is known for its high availability, scalability, and resilience; the downside is that it’s also notoriously complex to set up and manage.

In our previous article, we looked at augmenting our dashboard to store and display individual events from the Avengers using DataStax Astra, a serverless DBaaS powered by Apache Cassandra using Stargate to offer additional APIs for working with it.

Example: Apache Cassandra, CouchDB.

For our TikTok database, we’re using DataStax Astra DB: a cloud-based database that fully manages Apache Cassandra®, one of the most robust and scalable NoSQL databases around.

Data partitioning in Apache Cassandra.