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dremio-oss discussion
dremio-oss reviews and mentions
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Shades of Open Source - Understanding The Many Meanings of "Open"
This practice, in itself, isn't inherently bad. Many businesses maintain commercial proprietary forks of open-source projects, but usually, the commercial version has a different name than the open-source project. For example, in the world of data catalogs, Dremio is the main developer of Nessie, and Snowflake drives Polaris. Both aim to become community-driven projects over time but will also drive integrated features in their respective commercial products under different names. For instance, if you set up your own Nessie catalog, it has a distinct name compared to the Dremio Enterprise Catalog (formerly Arctic) integrated into Dremio Cloud. The Dremio Enterprise Catalog is powered by Nessie but has additional features, so the different names prevent confusion about available features or which documentation to reference.
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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.
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A note from our sponsor - CodeRabbit
coderabbit.ai | 13 Dec 2024
Stats
dremio/dremio-oss is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of dremio-oss is Java.