dremio-oss
Trino
dremio-oss | Trino | |
---|---|---|
8 | 44 | |
1,301 | 9,576 | |
0.8% | 1.8% | |
4.0 | 10.0 | |
13 days ago | 5 days ago | |
Java | Java | |
Apache License 2.0 | Apache License 2.0 |
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dremio-oss
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What is the separation of storage and compute in data platforms and why does it matter?
Dremio - Dremio is a data lakehouse based on the open-source Apache Iceberg table format. It offers different compute instances to process data that lives in your S3 bucket. You pay for S3 storage independently.
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What is dremio query engine
Dremio core is actually fully open source: https://github.com/dremio/dremio-oss
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Q – Run SQL Directly on CSV or TSV Files
I have been using Dremio to query large volume of CSV files: https://docs.dremio.com/software/data-sources/files-and-dire...
Although having them in some columnar format is much better for fast responses.
GitHub: https://github.com/dremio/dremio-oss
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Hands-On Introduction to Apache Iceberg - Data Lakehouse Engineering
As a Developer Advocate for Dremio I spend a lot of time doing research on technology and best practices around engineering Data Lakehouses and sharing what I learn through content for Subsurface - The Data Lakehouse Community. One of the major topics I've been diving deep into is the topic of Data Lakehouse Table Formats, these allow you to take the files on your data lake and group them into tables data processing engines like Dremio can operate on.
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Introduction to The World of Data - (OLTP, OLAP, Data Warehouses, Data Lakes and more)
Hearing about all these components sounds great, but what everyone wants isn't to have to setup and configure all these components but instead have a platform and tool that brings this all together in an easy to use package, and that platform is Dremio. With Dremio you can work with the data directly from your data lake. No copies, easy access, high performance.
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Data Lakehouse and Delta Lake
And as u/pych_phd said, it's not just Databricks, Snowflake and Azure who make these claims, even AWS, GCP, Dremio and I'm sure many others are too.
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Data Science Competition
Dremio
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Build your own “data lake” for reporting purposes
For my home projects I generate parquet (columnar and very well suited for DW like queries) files with pyarrow and use https://github.com/dremio/dremio-oss (https://www.dremio.com/on-prem/) to query them on lake (minio or just local disk or s3) and use Apache Superset for quick charts or dashboards.
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.
What are some alternatives?
presto - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io) [Moved to: https://github.com/trinodb/trino]
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
ClickHouse - ClickHouse® is a free analytics DBMS for big data
Presto - The official home of the Presto distributed SQL query engine for big data
Greenplum - Greenplum Database - Massively Parallel PostgreSQL for Analytics. An open-source massively parallel data platform for analytics, machine learning and AI.
Apache Drill - Apache Drill is a distributed MPP query layer for self describing data
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Apache Calcite - Apache Calcite
Rakam - 📈 Collect customer event data from your apps. (Note that this project only includes the API collector, not the visualization platform)
sgr - sgr (command line client for Splitgraph) and the splitgraph Python library
spring-data-jpa-mongodb-expressions - Use the MongoDB query language to query your relational database, typically from frontend.