cobrix VS delta

Compare cobrix vs delta and see what are their differences.


A COBOL parser and Mainframe/EBCDIC data source for Apache Spark (by AbsaOSS)


An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs (by delta-io)
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cobrix delta
1 69
133 6,958
0.0% 2.2%
8.2 9.8
25 days ago 4 days ago
Scala Scala
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.


Posts with mentions or reviews of cobrix. We have used some of these posts to build our list of alternatives and similar projects.


Posts with mentions or reviews of delta. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-19.
  • Delta Lake vs. Parquet: A Comparison
    2 projects | | 19 Jan 2024
    Delta is pretty great, let's you do upserts into tables in DataBricks much easier than without it.

    I think the website is here:

  • Understanding Parquet, Iceberg and Data Lakehouses
    4 projects | | 29 Dec 2023
    I often hear references to Apache Iceberg and Delta Lake as if they’re two peas in the Open Table Formats pod. Yet…

    Here’s the Apache Iceberg table format specification:

    As they like to say in patent law, anyone “skilled in the art” of database systems could use this to build and query Iceberg tables without too much difficulty.

    This is nominally the Delta Lake equivalent:

    I defy anyone to even scope out what level of effort would be required to fully implement the current spec, let alone what would be involved in keeping up to date as this beast evolves.

    Frankly, the Delta Lake spec reads like a reverse engineering of whatever implementation tradeoffs Databricks is making as they race to build out a lakehouse for every Fortune 1000 company burned by Hadoop (which is to say, most of them).

    My point is that I’ve yet to be convinced that buying into Delta Lake is actually buying into an open ecosystem. Would appreciate any reassurance on this front!

  • Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog
    4 projects | | 18 Dec 2023
    Apache Iceberg is one of the three types of lakehouse, the other two are Apache Hudi and Delta Lake.
  • [D] Is there other better data format for LLM to generate structured data?
    1 project | /r/MachineLearning | 10 Dec 2023
    The Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's over json.
  • Delta vs Iceberg: make love not war
    1 project | /r/MicrosoftFabric | 30 Jun 2023
    Delta 3.0 extends an olive branch.
  • Databricks Strikes $1.3B Deal for Generative AI Startup MosaicML
    4 projects | | 26 Jun 2023
    Databricks provides Jupyter lab like notebooks for analysis and ETL pipelines using spark through pyspark, sparkql or scala. I think R is supported as well but it doesn't interop as well with their newer features as well as python and SQL do. It interfaces with cloud storage backend like S3 and offers some improvements to the parquet format of data querying that allows for updating, ordering and merged through . They integrate pretty seamlessly to other data visualisation tooling if you want to use it for that but their built in graphs are fine for most cases. They also have ML on rails type through menus and models if I recall but I typically don't use it for that. I've typically used it for ETL or ELT type workflows for data that's too big or isn't stored in a database.
  • The "Big Three's" Data Storage Offerings
    2 projects | /r/dataengineering | 15 Jun 2023
    Structured, Semi-structured and Unstructured can be stored in one single format, a lakehouse storage format like Delta, Iceberg or Hudi (assuming those don't require low-latency SLAs like subsecond).
  • Ideas/Suggestions around setting up a data pipeline from scratch
    3 projects | /r/dataengineering | 9 Jun 2023
    As the data source, what I have is a gRPC stream. I get data in protobuf encoded format from it. This is a fixed part in the overall system, there is no other way to extract the data. We plan to ingest this data in delta lake, but before we do that there are a few problems.
  • Medallion/lakehouse architecture data modelling
    1 project | /r/dataengineering | 3 Jun 2023
    Take a look at Delta Lake, it enables a lot of database-like actions on files
  • CSV or Parquet File Format
    3 projects | /r/Python | 1 Jun 2023
    I prefer parquet (or delta for larger datasets. CSV for very small datasets, or the ones that will be later used/edited in Excel or Googke sheets.

What are some alternatives?

When comparing cobrix and delta you can also consider the following projects:

Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing

dvc - 🦉 ML Experiments and Data Management with Git

SynapseML - Simple and Distributed Machine Learning

Apache Cassandra - Mirror of Apache Cassandra

spark-nlp - State of the Art Natural Language Processing

lakeFS - lakeFS - Data version control for your data lake | Git for data

COBOL-Guide - COBOL Guide

hudi - Upserts, Deletes And Incremental Processing on Big Data.

unlock-mainframe-data-files-on-aws - This solution is designed to help you unlock legacy mainframe data by migrating data files from mainframe systems to AWS. By migrating the data, you can make use of the powerful analytics, machine learning, and other services available in AWS to gain insights and make better decisions based on the data.

delta-rs - A native Rust library for Delta Lake, with bindings into Python

superbol-studio-oss - Open-Source part of the SuperBOL Studio, including the Vscode mode with LSP

iceberg - Apache Iceberg