Trino
dremio-oss
Our great sponsors
Trino | dremio-oss | |
---|---|---|
44 | 8 | |
9,408 | 1,290 | |
3.0% | 1.6% | |
10.0 | 4.0 | |
3 days ago | 2 months ago | |
Java | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Trino
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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.
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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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Apache Iceberg as storage for on-premise data store (cluster)
Trino or Hive for SQL querying. Get Trino/Hive to talk to Nessie.
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Uber Interview Experience/Asking Suggestions
One place to look are the projects repo's and docs, once you have a good idea of how the system is architected poking around pieces of the codebase can be helpful in letting you really understand their internals. I personally enjoy going through spark repo and trino repo and the documentation for both projects is decent and can answer many of your questions.
- Java OSS with best code quality you’ve ever seen?
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What is the separation of storage and compute in data platforms and why does it matter?
However, once your data reaches a certain size or you reach the limits of vertical scaling, it may be necessary to distribute your queries across a cluster, or scale horizontally. This is where distributed query engines like Trino and Spark come in. Distributed query engines make use of a coordinator to plan the query and multiple worker nodes to execute them in parallel.
- Sparkless is born
- Why use Spark at all?
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Data Engineer Github Profile?
So, there are a lot of people involved which is why you try to find some common ground regarding coding style, documentation, programming language version, … Most larger project have some guidelines you can read to see what is necessary for a PR to be approved: Trino’s Guidelines or dbt.
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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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.
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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.
What are some alternatives?
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Presto - The official home of the Presto distributed SQL query engine for big data
Apache Drill - Apache Drill is a distributed MPP query layer for self describing data
Apache Calcite - Apache Calcite
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.
Apache Flink - Apache Flink
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]
kyuubi - Apache Kyuubi is a distributed and multi-tenant gateway to provide serverless SQL on data warehouses and lakehouses.
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
hudi - Upserts, Deletes And Incremental Processing on Big Data.
clickhousedb_fdw - PostgreSQL's Foreign Data Wrapper For ClickHouse