Apache Parquet VS delta

Compare Apache Parquet vs delta and see what are their differences.

delta

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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Apache Parquet delta
4 69
2,374 6,782
2.8% 1.9%
9.2 9.8
about 8 hours ago 6 days ago
Java 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.
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.

Apache Parquet

Posts with mentions or reviews of Apache Parquet. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-11.
  • How-to-Guide: Contributing to Open Source
    19 projects | /r/dataengineering | 11 Jun 2022
    Apache Parquet
  • parquet-tools
    3 projects | /r/golang | 23 Jan 2022
    This go implementation, other than common advantages from go itself (small single executable, support multiple platforms, speed, etc.), has some neat features compare with Java parquet tool and Python one like:
  • Writing Apache Parquet Files
    2 projects | /r/androiddev | 30 May 2021
    Hi, I've been trying to write parquet files on android for the past couple of days, and have really been struggling to find a solution. My original hypothesis was to just use the java parquet implementation (https://github.com/apache/parquet-mr), but I've since realized that not all java libraries play well with Android. I've gone through essentially dependency hell trying to franken-fit the library into my project, and imported as much as i could before hitting walls such as this one (https://github.com/mockito/mockito/issues/841).
  • pqrs: A parquet-tools replacement in Rust using Apache Arrow
    2 projects | /r/dataengineering | 18 Feb 2021
    Like many of you probably do, I tend to work with Parquet files a lot. parquet-tools has been my tool of choice for inspecting parquet files, but that has been deprecated recently. So, I created a replacement for it using Rust and Apache Arrow.

delta

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 | news.ycombinator.com | 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: https://delta.io

  • Understanding Parquet, Iceberg and Data Lakehouses
    4 projects | news.ycombinator.com | 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:

    https://iceberg.apache.org/spec/

    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:

    https://github.com/delta-io/delta/blob/master/PROTOCOL.md

    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 | dev.to | 18 Dec 2023
    Apache Iceberg is one of the three types of lakehouse, the other two are Apache Hudi and Delta Lake.
  • Databricks Strikes $1.3B Deal for Generative AI Startup MosaicML
    4 projects | news.ycombinator.com | 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 https://delta.io . 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.
  • 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.
  • How to build a data pipeline using Delta Lake
    2 projects | dev.to | 19 May 2023
    This sounds like a new trending destination to take selfies in front of, but it’s even better than that. Delta Lake is an “open-source storage layer designed to run on top of an existing data lake and improve its reliability, security, and performance.” (source). It let’s you interact with an object storage system like you would with a database.
  • Delta.io/deltalake self hosting
    2 projects | /r/bigdata | 26 Apr 2023
    I mean the different between using the delta.io framework to let it run on your own machines/ vms vs using databricks and have clusters defined.
    2 projects | /r/bigdata | 26 Apr 2023
    You are right, delta.io is just a framework. Sorry for the unclear question. Another try: when you host spark on your own with delta as table format compared to usage of Databricks, what are the differences?

What are some alternatives?

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

Protobuf - Protocol Buffers - Google's data interchange format

Apache Thrift - Apache Thrift

dvc - 🦉 ML Experiments and Data Management with Git

Apache Avro - Apache Avro is a data serialization system.

Apache Cassandra - Mirror of Apache Cassandra

Apache Orc - Apache ORC - the smallest, fastest columnar storage for Hadoop workloads

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

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

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

iceberg - Apache Iceberg

Big Queue - A big, fast and persistent queue based on memory mapped file.

Persistent Collection - A Persistent Java Collections Library