18 Ratings
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Score 7.4 out of 101
16 Ratings
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Score 8.7 out of 101

Likelihood to Recommend

Apache Pig

It is one great option in terms of database pipelining. It is highly effective for unstructured datasets to work with. Also, Apache Pig being a procedural language, unlike SQL, it is also easy to learn compared to other alternatives. But other alternatives like Apache Spark would be my recommendation due to the high availability of advanced libraries, which will reduce our extra efforts of writing from scratch
Kartik Chavan profile photo

Databricks Unified Analytics Platform

Databricks has helped my teams write PySpark and Spark SQL jobs and test them out before formally integrating them in Spark jobs. Through Databricks we can create parquet and JSON output files. Datamodelers and scientists who are not very good with coding can get good insight into the data using the notebooks that can be developed by the engineers.
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Feature Rating Comparison

Platform Connectivity

Apache Pig
Databricks Unified Analytics Platform
8.3
Connect to Multiple Data Sources
Apache Pig
Databricks Unified Analytics Platform
9.0
Extend Existing Data Sources
Apache Pig
Databricks Unified Analytics Platform
9.0
Automatic Data Format Detection
Apache Pig
Databricks Unified Analytics Platform
7.0

Data Exploration

Apache Pig
Databricks Unified Analytics Platform
6.0
Visualization
Apache Pig
Databricks Unified Analytics Platform
6.0
Interactive Data Analysis
Apache Pig
Databricks Unified Analytics Platform
6.0

Data Preparation

Apache Pig
Databricks Unified Analytics Platform
8.0
Interactive Data Cleaning and Enrichment
Apache Pig
Databricks Unified Analytics Platform
8.0
Data Transformations
Apache Pig
Databricks Unified Analytics Platform
9.0
Data Encryption
Apache Pig
Databricks Unified Analytics Platform
7.0
Built-in Processors
Apache Pig
Databricks Unified Analytics Platform
8.0

Platform Data Modeling

Apache Pig
Databricks Unified Analytics Platform
8.3
Multiple Model Development Languages and Tools
Apache Pig
Databricks Unified Analytics Platform
9.0
Automated Machine Learning
Apache Pig
Databricks Unified Analytics Platform
8.0
Single platform for multiple model development
Apache Pig
Databricks Unified Analytics Platform
9.0
Self-Service Model Delivery
Apache Pig
Databricks Unified Analytics Platform
7.0

Model Deployment

Apache Pig
Databricks Unified Analytics Platform
7.5
Flexible Model Publishing Options
Apache Pig
Databricks Unified Analytics Platform
7.0
Security, Governance, and Cost Controls
Apache Pig
Databricks Unified Analytics Platform
8.0

Pros

Apache Pig

  • Apache pig DSL provides a better alternative to Java map reduce code and the instruction set is very easy to learn and master.
  • It has many advanced features built-in such as joins, secondary sort, many optimizations, predicate push-down, etc.
  • When Hive was not very advanced (extremely slow) few years ago, pig has always been the go to solution. Now with Spark and Hive (after significant updates), the need to learn apache pig may be questionable.
No photo available

Databricks Unified Analytics Platform

  • Extremely Flexible in Data Scenarios
  • Fantastic Performance
  • DB is always updating the system so we can have latest features.
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Cons

Apache Pig

  • Improve Spark support and compatibility
  • Spark and Hive are already being used main-stream, both of them have an instruction set that is easier to learn and master in a matter of days. While apache pig used to be a great alternative to writing java map reduce, Hive after significant updates is now either equal or better than pig.
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Databricks Unified Analytics Platform

  • The navigation through which one would create a workspace is a bit confusing at first. It takes a couple minutes to figure out how to create a folder and upload files since it is not the same as traditional file systems such as box.com
  • Also, when you create a table, if you forgot to copy the link where the table is stored, it is hard to relocate it. Most of the time I would have to delete the table and re-created.
Ann Le profile photo

Usability

Apache Pig

Apache Pig 10.0
Based on 1 answer
It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.
Subhadipto Poddar profile photo

Databricks Unified Analytics Platform

Databricks Unified Analytics Platform 9.0
Based on 1 answer
This has been very useful in my organization for shared notebooks, integrated data pipeline automation and data sources integrations. Integration with AWS is seamless. Non tech users can easily learn how to use Databricks. You can have your company LDAP connect to it for login based access controls to some extent
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Alternatives Considered

Apache Pig

I use both Apache Pig and its alternatives like Apache Spark & Apache Hive. Apache Pig was one of the best options in Big Data's initial stages. But now alternatives have taken over the market, rendering Apache Pig behind in the competition. But it is still a better alternative to Map Reduce. It is also a good option for working with unstructured datasets. Moreover, in certain cases, Apache Pig is much faster than Hive & Spark.
Kartik Chavan profile photo

Databricks Unified Analytics Platform

I also use Microsoft Azure Machine Learning in parallel with Databricks. They use different file formats which teach me to be flexible and able to write different programs. They are equally useful to me and I would like to master both platforms for any future usage. I do prefer Databricks because it could be free if I decided to go with the Databricks Community Edition only.
Ann Le profile photo

Return on Investment

Apache Pig

  • Return on Investments are significant considering what it can do with traditional analysis techniques. But, other alternatives like Apache Spark, Hive being more efficient, it is hard to stick to Apache Pig.
  • It can handle large datasets pretty easily compared to SQL. But, again, alternatives are more efficient.
  • While working on unstructured, decentralized dataset, Pig is highly beneficial, as it is not a complete deviation from SQL, but it does not take you in complexity MapReduce as well.
Kartik Chavan profile photo

Databricks Unified Analytics Platform

  • Quick adoption of cloud services by end users
  • Cost is high
No photo available

Pricing Details

Apache Pig

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Databricks Unified Analytics Platform

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

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