delta-rs
delta-oss
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delta-rs
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Delta Lake vs. Parquet: A Comparison
I work at Databricks, but am pretty must just an OSS nerd, mainly focusing on Delta Rust recently: https://github.com/delta-io/delta-rs
I did some keyword research and wrote this post cause lots of folks are doing searches for Delta Lake vs Parquet. I'm just trying to share a fair summary of the tradeoffs with folks who are doing this search. It's a popular post and that's why I figured I would share it here.
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Working with Rust
Seeing a lot of great libraries coming out with python bindings in the data world e.g delta-rs Polars. I see it growing in this space as a C++ alternative
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Ideas/Suggestions around setting up a data pipeline from scratch
If I’m not misunderstanding, you could both decode the gRPC protobuf AND write to delta lake in Rust. Tonic, Delta-rs.
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Polars query engine 0.29.0 released
I know someone will be adding this on the python side in the coming weeks. On the rust side you can use delta-rs with polars. Though you would be compiling both arrow2 and arrow-rs, so that's quite heavy.
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Delta Lake without Databricks?
You don’t need DBX to use Delta Lake. You can use S3 as the backend and just use the Python Delta Lake library. It works great! https://github.com/delta-io/delta-rs
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Seeking Recommendations for a Master Data Management Tool
Maybe if I get some free time soon I can formalize into a working example. Been wanting an excuse to try similar concept in delta-rs and polars/duckdb vs databricks/spark vs iceberg/polars.
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How to write Python extensions in Rust with PyO3
PyO3 is being used to expose the Python bindings to the delta-rs project: https://github.com/delta-io/delta-rs
It's a great way to expose Python bindings because it "feels" Pythonic. Most users run pip install deltalake and are completely unaware that the backend is implemented in Rust.
This is quite a different user experience than Python bindings for Java backends exposed via py4j. The py4j interfaces have the Java feel and require Java to be installed, which most Python users don't like.
- Delta without using Spark
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Spark open source community is awesome
Yea, there are tons of employees from companies that have made massive contributions to the Spark ecosystem. Apple built Delta Lake with Databricks, see this video for more detail. Lots of Spark PMCs are from various companies. delta-rs was initially built by Scribd and is now actively maintained by engineers at Voltron & other companies. It's awesome the community has so many contributors from various sources.
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Snowpark equivalent on Databricks?
Have a look at this https://delta-io.github.io/delta-rs/python/
delta-oss
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Databricks Is an RDBMS
https://github.com/delta/delta-oss
link seems to be broken.
only in name. check out the lack of traction for a lot of PRs on https://github.com/delta/delta-oss . Iceberg (https://iceberg.apache.org) is comparable but actually OSS.
What are some alternatives?
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
roapi - Create full-fledged APIs for slowly moving datasets without writing a single line of code.
materialize - The data warehouse for operational workloads.
ballista - Distributed compute platform implemented in Rust, and powered by Apache Arrow.
kafka-delta-ingest - A highly efficient daemon for streaming data from Kafka into Delta Lake
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
databricks-cli - The missing command line client for Databricks SQL
dipa - dipa makes it easy to efficiently delta encode large Rust data structures.
connectors - This library allows Scala and Java-based projects (including Apache Flink, Apache Hive, Apache Beam, and PrestoDB) to read from and write to Delta Lake.
sops - Simple and flexible tool for managing secrets
delta-sharing-rs - A Minimalistic Rust Implementation of Delta Sharing Server.