Trino VS Apache Cassandra

We decided not to waste time reinventing the wheel and simply installed Trino on our servers. It’s a full featured SQL query engine that works on your data. Now our analysts can use it to work with data from AppMetr and execute queries at different levels of complexity.

DevRel for StarRocks. Trino doesn't have a great caching layer (https://github.com/trinodb/trino/pull/16375) and performance (https://github.com/trinodb/trino/issues/14237) and https://github.com/oap-project/Gluten-Trino. In benchmarks and community user testing, StarRocks has outperformed.

What if my SQL engine is Presto, Trino [1], or a similar query engine? If it's federating multiple source databases we peel the SQL back and get... SQL? Or you peel the SQL back and get... S3 + Mongo + Hadoop? Junior analysts would work at 1/10th the speed if they had to use those raw.

[1] https://trino.io/

The good thing is that the concepts in terms to the SQL supported by Trino transfers between them all. So its completely reasonable to start with one and move to another. In fact that is something that happens regularly. I invite to you check out the talks from the Trino Fest event that is just wrapping up today. There are presentations about all these aspects and different scenarios users encounter. All videos and slides will go live on the Trino website soon. Also feel free to join the Trino slack to chat about about all this with other users.

There are distributed query engines like Trino that help with this sort of problem https://trino.io/

This issue in particular is a killer for me: https://github.com/trinodb/trino/issues/10974

AFAIK Presto was forked and Trino https://trino.io/ is now the leading SQL Query engine .

Trino or Hive for SQL querying. Get Trino/Hive to talk to Nessie.

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.