Trino
trino_data_mesh
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| Trino | trino_data_mesh | |
|---|---|---|
| 44 | 1 | |
| 9,552 | 8 | |
| 3.1% | - | |
| 10.0 | 1.8 | |
| 4 days ago | almost 3 years ago | |
| Java | ||
| Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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Trino
- Trino: Fast distributed SQL query engine for big data analytics
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Game analytic power: how we process more than 1 billion events per day
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.
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Your Thoughts on OLAPs Clickhouse vs Apache Druid vs Starrocks in 2023/2024
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.
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Making Hard Things Easy
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/
- Trino, a open query engine that runs at ludicrous speed
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Questions about Athena, Trino and Iceberg
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.
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Multi-Databases across Multiple Servers - MySQL
There are distributed query engines like Trino that help with this sort of problem https://trino.io/
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Iceberg on Cloudtrail Logs with Athena
This issue in particular is a killer for me: https://github.com/trinodb/trino/issues/10974
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Data Lake, Real-time Analytics, or Both? Exploring Presto and ClickHouse
AFAIK Presto was forked and Trino https://trino.io/ is now the leading SQL Query engine .
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Apache Iceberg as storage for on-premise data store (cluster)
Trino or Hive for SQL querying. Get Trino/Hive to talk to Nessie.
trino_data_mesh
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What even is data mesh
Not central to the main ideas of this article, but if you want to have a data mesh that is self-service, why force folks to use a particular storage medium like a data warehouse? That still requires centralization of the data.
Why not instead have a tool like Trino (https://trino.io) that allows you to let different domains use whatever datastore they happen to use. You still would need to enforce schema, but this can be done in tools like schema registry as mentioned in the article along with a data cataloging tool.
These tools facilitate the distributed nature of the problem nicely and encourage healthy standards to be discussed and the formalized in schema definitions and catalogs that remove the ambiguity of discourse and documentation.
Nice example is laid out in this repo of how Trino can accomplish data mesh principles 1 and 3 (https://github.com/findinpath/trino_data_mesh).
What are some alternatives?
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
dremio-oss - Dremio - the missing link in modern data
lightdash - Self-serve BI to 10x your data team ⚡️
Presto - The official home of the Presto distributed SQL query engine for big data
dbt-customer-journey-analysis - Using DBT for Customer Journey Analysis on RudderStack - an open-source, warehouse-first customer data pipeline and Segment alternative.
Apache Drill - Apache Drill is a distributed MPP query layer for self describing data
dbt-spotify-analytics - Containerized end-to-end analytics of Spotify data using Python, dbt, Postgres, and Metabase
Apache Calcite - Apache Calcite
dbt-sessionization - Using DBT for Creating Session Abstractions on RudderStack - an open-source, warehouse-first customer data pipeline and Segment alternative.
ClickHouse - ClickHouse® is a free analytics DBMS for big data
spring-data-jpa-mongodb-expressions - Use the MongoDB query language to query your relational database, typically from frontend.