Software Alternatives & Reviews

Apache Parquet VS Delta Lake

Compare Apache Parquet VS Delta Lake and see what are their differences

Apache Parquet logo Apache Parquet

Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.

Delta Lake logo Delta Lake

Application and Data, Data Stores, and Big Data Tools
  • Apache Parquet Landing page
    Landing page //
    2022-06-17
  • Delta Lake Landing page
    Landing page //
    2023-08-26

Apache Parquet videos

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Delta Lake videos

A Thorough Comparison of Delta Lake, Iceberg and Hudi

More videos:

  • Tutorial - Delta Lake for apache Spark | How does it work | How to use delta lake | Delta Lake for Spark ACID
  • Review - ACID ORC, Iceberg, and Delta Lake—An Overview of Table Formats for Large Scale Storage and Analytics

Category Popularity

0-100% (relative to Apache Parquet and Delta Lake)
Databases
56 56%
44% 44
Development
0 0%
100% 100
Big Data
100 100%
0% 0
Office & Productivity
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Delta Lake should be more popular than Apache Parquet. It has been mentiond 31 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Parquet mentions (19)

  • [D] Is there other better data format for LLM to generate structured data?
    The Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's delta.io over json. Source: 5 months ago
  • Demystifying Apache Arrow
    Apache Parquet (Parquet for short), which nowadays is an industry standard to store columnar data on disk. It compress the data with high efficiency and provides fast read and write speeds. As written in the Arrow documentation, "Arrow is an ideal in-memory transport layer for data that is being read or written with Parquet files". - Source: dev.to / 12 months ago
  • Parquet: more than just "Turbo CSV"
    Googling that suggests this page: https://parquet.apache.org/. Source: about 1 year ago
  • Beginner question about transformation
    You should also consider distribution of data because in a company that has machine learning workflows, the same data may need to go through different workflows using different technologies and stored in something other than a data warehouse, e.g. Feature engineering in Spark and loaded/stored in binary format such as Parquet in a data lake/object store. Source: about 1 year ago
  • Pandas Free Online Tutorial In Python — Learn Pandas Basics In 5 Lessons!
    This section will teach you how to read and write data to and from a variety of file types, including CSV, Excel, SQL, HTML, Parquet, JSON etc. You’ll also learn how to manipulate data from other sources, such as databases and web sites. Source: about 1 year ago
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Delta Lake mentions (31)

  • Delta Lake vs. Parquet: A Comparison
    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. - Source: Hacker News / 4 months ago
  • Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog
    Apache Iceberg is one of the three types of lakehouse, the other two are Apache Hudi and Delta Lake. - Source: dev.to / 5 months ago
  • [D] Is there other better data format for LLM to generate structured data?
    The Apache Spark / Databricks community prefers Apache parquet or Linux Fundation's delta.io over json. Source: 5 months ago
  • Databricks Strikes $1.3B Deal for Generative AI Startup MosaicML
    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... - Source: Hacker News / 11 months ago
  • The "Big Three's" Data Storage Offerings
    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). Source: 11 months ago
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What are some alternatives?

When comparing Apache Parquet and Delta Lake, you can also consider the following products

Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

GeoSpock - GeoSpock is the platform for data lake management, providing a unified view of the data assets within an organization and making it easily accessible.

Apache ORC - Apache ORC is a columnar storage for Hadoop workloads.

Cloud Dataprep - Cloud Dataprep by Trifacta is a data prep & cleansing service for exploring, cleaning & preparing datasets using a simple drag & drop browser environment