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Apache Parquet VS Apache Pig

Compare Apache Parquet VS Apache Pig 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.

Apache Pig logo Apache Pig

Pig is a high-level platform for creating MapReduce programs used with Hadoop.
  • Apache Parquet Landing page
    Landing page //
    2022-06-17
  • Apache Pig Landing page
    Landing page //
    2021-12-31

Apache Parquet videos

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Apache Pig videos

Pig Tutorial | Apache Pig Script | Hadoop Pig Tutorial | Edureka

More videos:

  • Review - Simple Data Analysis with Apache Pig

Category Popularity

0-100% (relative to Apache Parquet and Apache Pig)
Databases
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Big Data
100 100%
0% 0
Database Tools
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Parquet should be more popular than Apache Pig. It has been mentiond 20 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 (20)

  • Shades of Open Source - Understanding The Many Meanings of "Open"
    It's this kind of certainty that underscores the vital role of the Apache Software Foundation (ASF). Many first encounter Apache through its pioneering project, the open-source web server framework that remains ubiquitous in web operations today. The ASF was initially created to hold the intellectual property and assets of the Apache project, and it has since evolved into a cornerstone for open-source projects... - Source: dev.to / 4 days 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: 6 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 / about 1 year 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: over 1 year ago
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Apache Pig mentions (2)

  • In One Minute : Hadoop
    Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / over 1 year ago
  • Spark is lit once again
    In the early days of the Big Data era when K8s hasn't even been born yet, the common open source go-to solution was the Hadoop stack. We have written several old-fashioned Map-Reduce jobs, scripts using Pig until we came across Spark. Since then Spark has became one of the most popular data processing engines. It is very easy to start using Lighter on YARN deployments. Just run a docker with proper configuration... - Source: dev.to / over 2 years ago

What are some alternatives?

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

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

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

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

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.

Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)