Trino VS dbt-databricks

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.

Our current data infra looks a little something like this: 1. Airbyte deployed on EKS for supported data connectors. I’m using the alpha Databricks connector to load directly into Unity Catalog. 1a. S3 bucket for raw landing zone storage if we cannot directly load into Databricks Managed Tables. 2. Orchestration, storage, and transformations are in Databricks. Calling out to the Airbyte api in the EKS cluster to keep all orchestrations inside Databricks. 2a. databricks-dbt for transformations & cleaning.

dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA)

Read this https://github.com/databricks/dbt-databricks

Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose.

Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake.

databricks

Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward.