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Apache Pig

Pig Alternatives & Competitors

(21)3.9 out of 5

Looking for alternatives to Apache Pig? Tons of people want Big Data Analytics Software to help with data lake, spark integration, and governed discovery. What's difficult is finding out whether or not the software you choose is right for you. We have compiled a list of Big Data Analytics Software that reviewers voted best overall compared to Apache Pig. Based on reviewer data you can see how Apache Pig stacks up to the competition, check reviews from current & previous users, and find the best fit for your business. Qlik Sense, MATLAB, Google BigQuery, and Qubole are the most popular alternatives and competitors to Apache Pig.

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Top Alternatives to Apache Pig

  • Qlik Sense
  • MATLAB
  • Google BigQuery
  • Qubole
  • Alteryx

Top 20 Alternatives & Competitors to Apache Pig

Browse options below. Based on reviewer data you can see how Apache Pig stacks up to the competition, check reviews from current & previous users in industries like Computer Software, Internet, and Information Technology and Services, and find the best product for your business.
    #1
  1. Qlik Sense

    (413)4.4 out of 5
  2. Qlik Sense is a revolutionary self-service data visualization and discovery application designed for individuals, groups and organizations.

    Categories in common with Pig:
    AH
    Enterprise level integration, Version control, Security

    Reviewers say compared to Apache Pig, Qlik Sense is:

    More expensive
    Better at support
    More usable
    #2
  3. MATLAB

    (565)4.5 out of 5
  4. MATLAB is a programming, modeling and simulation tool developed by MathWorks.

    Categories in common with Pig:
    UI
    I started to use Matlab at the University and I love it since then. I even did my Master thesis using it and created some new algorithms that were publish on a paper. Super easy to learn and to use.

    Reviewers say compared to Apache Pig, MATLAB is:

    More expensive
    Better at support
    Better at meeting requirements
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    #3
  5. Google BigQuery

    (282)4.4 out of 5
    Optimized for quick response
  6. Analyze Big Data in the cloud with BigQuery. Run fast, SQL-like queries against multi-terabyte datasets in seconds. Scalable and easy to use, BigQuery gives you real-time insights about your data.

    Categories in common with Pig:
    Brent S.
    BS
    Bigquery builds upon my knowledge of SQL, plus takes advantage of my python skills as well. Which give me the flexibility to provide customized solutions.

    Reviewers say compared to Apache Pig, Google BigQuery is:

    More expensive
    Better at support
    Better at meeting requirements
    #4
  7. Qubole

    (257)4.0 out of 5
    Optimized for quick response
  8. Qubole delivers a Self-Service Platform for Big Data Analytics built on Amazon, Microsoft and Google Clouds

    Categories in common with Pig:
    UC
    My main like is their portal, which helps to dig in history and provide references. Given the variety of data processing engines offers flavors on need basis. And their customer support.

    Reviewers say compared to Apache Pig, Qubole is:

    More expensive
    Better at support
    Better at meeting requirements
    #5
  9. Alteryx

    (142)4.5 out of 5
  10. Alteryx provides Strategic Analytics & Agile BI for companies making strategic business decisions using a variety of data sources. Data artisans unite.

    Categories in common with Pig:
    Luis M.
    LM
    I like the ease of it and how simple it makes it to manipulate data.

    Reviewers say compared to Apache Pig, Alteryx is:

    More expensive
    Better at support
    Easier to set up
    #6
  11. Azure Databricks

    (106)4.4 out of 5
  12. Accelerate innovation by enabling data science with a high-performance analytics platform that's optimized for Azure.

    Categories in common with Pig:
    Debaraj B.
    DB
    Well, it uses Apache Spark, that's 100 times faster than Hadoop. With the transformations and actions that can be done here on data, it should be an obvious choice for anyone handling Big...Read more

    Reviewers say compared to Apache Pig, Azure Databricks is:

    More expensive
    Better at support
    Easier to set up
    #7
  13. Cloudera

    (25)4.1 out of 5
  14. Cloudera Enterprise Core provides a single Hadoop storage and management platform that natively combines storage, processing and exploration for the enterprise.

    Categories in common with Pig:
    AI
    The ability to monitor and manage numerous Hadoop clusters from one tool. An easy to learn and use REST API and Python client library. Easy to use graphical interface to manage the health of our...Read more

    Reviewers say compared to Apache Pig, Cloudera is:

    More expensive
    Better at support
    Better at meeting requirements
    #8
  15. IBM Cloud Pak for Data

    (40)4.3 out of 5
    Optimized for quick response
  16. Your AI is only as good as the data that feeds it. With IBM Cloud Pak for Data, you can make your data ready for an AI and multi-cloud world and access an array of IBM Watson technologies at your fingertips. Rapidly provision services for data scientists, data engineers and developers so they can work faster than ever. Simplify hybrid data management, unified data governance and integration, data science and business analytics with a single solution.

    Categories in common with Pig:
    Miguel L.
    ML
    I really love auto ai and jupyter lab and machine learning

    Reviewers say compared to Apache Pig, IBM Cloud Pak for Data is:

    More expensive
    Better at support
    Better at meeting requirements
    #9
  17. Azure Data Lake Analytics

    (34)4.2 out of 5
  18. Azure Data Lake Analytics is a distributed, cloud-based data processing architecture offered by Microsoft in the Azure cloud. It is based on YARN, the same as the open-source Hadoop platform.

    Categories in common with Pig:
    Abhishek Y.
    AY
    Data lake allows to us to connect to various source like power bi,data bricks

    Reviewers say compared to Apache Pig, Azure Data Lake Analytics is:

    More expensive
    Better at support
    Better at meeting requirements
    #10
  19. TIBCO Data Science

    (40)3.8 out of 5
    Optimized for quick response
  20. Accelerate ROI from your data science initiatives with a collaborative analytic workflow builder that lets you transform data into insight within Hadoop and other big data environments. Unlock your data's hidden potential and increase the value of your big data infrastructure.

    Categories in common with Pig:
    PM
    In this exploring phase, The best thing about tibco data science is out of the box tool readily available

    Reviewers say compared to Apache Pig, TIBCO Data Science is:

    More expensive
    Better at support
    Better at meeting requirements
    #11
  21. Dash

    (30)4.8 out of 5
  22. Dash is the trusted solution for operationalizing Python and R models and is the fastest way to build interactive analytic apps. Dash empowers data science teams to focus on the data and models, while still producing and deploying enterprise-ready apps. What would typically require a team of back-end developers, front-end developers and IT can all be done with Dash.

    Categories in common with Pig:
    TB
    Creating figures that talk to one another e.g. selecting data in one figure immediately updates other figures.

    Reviewers say compared to Apache Pig, Dash is:

    Better at support
    Easier to set up
    Better at meeting requirements
    #12
  23. DIAdem

    (28)4.4 out of 5
  24. DIAdem is a single, unified software environment that makes you more efficient when post-processing your measurement data. DIAdem is optimized for large data sets and includes tools to help you quickly search for the data you need, view and investigate that data, transform it with engineering-specific analysis functions, and share results with a powerful drag-and-drop report editor. You can use scripts in DIAdem to automate your repetitive data post-processing tasks and efficiently transform your measurement data into valuable insights.

    Categories in common with Pig:
    MH
    Quite intuitive interface with data visualization options. Ability to learn fast and easy step in

    Reviewers say compared to Apache Pig, DIAdem is:

    More expensive
    Better at support
    Better at meeting requirements
    #13
  25. EXASOL

    (10)4.7 out of 5
  26. EXASOL is a high-performance, in-memory, MPP database specifically designed for in-memory analytics. From business-critical data applications to advanced analytics, the database helps you to analyze large volumes of data in real-time, helping you to accelerate your BI and reporting, and to turn data into value.

    Categories in common with Pig:
    WG
    EXASOL is an incredibly powerful database - its performance mean that I never have to worry about computational efficiency when designing analytics pipelines and can focus on building in complex...Read more

    Reviewers say compared to Apache Pig, EXASOL is:

    Better at support
    Better at meeting requirements
    More expensive
    #14
  27. Confluent

    (25)4.4 out of 5
  28. A stream data platform.

    Categories in common with Pig:
    Shekhar P.
    SP
    The best things of the confluent platform to use Apache Kafka is connectors. They provide a lot of connectors which we can use in our project without writing any single lines of code.

    Reviewers say compared to Apache Pig, Confluent is:

    More expensive
    Better at support
    Better at meeting requirements
    #15
  29. Dremio

    (21)4.8 out of 5
    Optimized for quick response
  30. Dremio is a data analysis software. It is self-service data platform provided that users discover, accelerate and share data at any time.

    Categories in common with Pig:
    AF
    Amazing performance with Apache Arrow at its core with new enhancements actively developed with the open source community such as Gandiva for optimized execution and Flight for optimized data...Read more

    Reviewers say compared to Apache Pig, Dremio is:

    Better at support
    More usable
    Better at meeting requirements
    #16
  31. Arcadia Enterprise

    (14)3.7 out of 5
    Optimized for quick response
  32. Arcadia Enterprise provides a visual analytics and BI platform native to big data platforms such as Apache Hadoop, Kafka, and the cloud.

    Categories in common with Pig:
    AT
    Easy to use and nice user interface

    Reviewers say compared to Apache Pig, Arcadia Enterprise is:

    More expensive
    Better at support
    Easier to set up
    #17
  33. DNIF - BIG DATA ANALYTICS

    (3)4.8 out of 5
  34. DNIF allows you to partition one data infrastructure and enable multiple teams to solve many challenges. DNIF makes it easy to have multiple users working and solving different problems using the same data layer

    Categories in common with Pig:
    AT
    The query response is very swift , which makes it easier and faster to hunt for things. Orchestration can accommodate any use case that we can think of. Integrated response can be set with any...Read more
    #18
  35. BellaDati

    (2)4.5 out of 5
  36. Agile analytics and reporting tool, which enables business users to make informed decisions from real-time business data

    Categories in common with Pig:
    UF
    Pure web application so no installation. A lot of data source connectors.
    #19
  37. Omniscope Evo

    (2)3.5 out of 5
  38. Omniscope Evo is a scalable streaming data blending, transformation/preparation tool including R-based high-performance analytics and interactive visual discovery and reporting.

    Categories in common with Pig:
    AI
    It is a great tools for data analysis and presentation. The ETL Data Manager is an absolute delight. It allows you to visualize and report large amount of data with appropriate maps, images, links...Read more
    #20
  39. Jethro

    (1)5.0 out of 5
  40. Jethro makes interactive Business Intelligence work on Big Data. (Hadoop). Jethro enables Business Intelligence users to analyze and visualize Big Data in real-time and its SQL Acceleration Engine seamlessly integrates with BI tools like Tableau or Qlik.

    Categories in common with Pig:
    Vivek Kumar A.
    VA
    Best integration with Hadoop and other big data platform.