Software Alternatives & Reviews

Apache Pig VS Apache Archiva

Compare Apache Pig VS Apache Archiva and see what are their differences

Apache Pig logo Apache Pig

Pig is a high-level platform for creating MapReduce programs used with Hadoop.

Apache Archiva logo Apache Archiva

Apache Archiva is an extensible repository management software.
  • Apache Pig Landing page
    Landing page //
    2021-12-31
  • Apache Archiva Landing page
    Landing page //
    2019-04-29

Apache Pig videos

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

More videos:

  • Review - Simple Data Analysis with Apache Pig

Apache Archiva videos

How to install and configure apache archiva in AWS EC2

More videos:

  • Review - Apache Archiva new UI Quick start

Category Popularity

0-100% (relative to Apache Pig and Apache Archiva)
Data Dashboard
100 100%
0% 0
App Reviews
0 0%
100% 100
Database Tools
100 100%
0% 0
Customer Feedback
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Pig and Apache Archiva

Apache Pig Reviews

We have no reviews of Apache Pig yet.
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Apache Archiva Reviews

Repository Management Tools
Archiva, yet another tool from the Apache family of software offerings – It is an extensible Repository management software that provides its help in taking care of the enterprise-wide build artifact repository. An incoming request with a virtual repository or a repository group URL – Archiva would look for the requested artifact from the repositories under that specific...
Source: mindmajix.com
What is Artifactory?
Archiva is an extensible repository management program that assists in the management of the enterprise-wide build artifact repository. It is another product from the Apache family of software solutions. An incoming request containing a virtual repository or a repository group URL would cause Archiva to search the repositories under that group for the requested artifact....

Social recommendations and mentions

Based on our record, Apache Pig seems to be more popular. It has been mentiond 2 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 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

Apache Archiva mentions (0)

We have not tracked any mentions of Apache Archiva yet. Tracking of Apache Archiva recommendations started around Mar 2021.

What are some alternatives?

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

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 Tika - Apache Tika toolkit detects and extracts metadata and text from different file types.

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.

code-prettify - Code Prettify is an embeddable script that makes source-code snippets in HTML prettier.

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

highlight.js - Highlight.js is a syntax highlighter written in JavaScript. It works in the browser as well as on the server.