18 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow'>trScore algorithm: Learn more.</a>
Score 7.3 out of 101
12 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow'>trScore algorithm: Learn more.</a>
Score 8.6 out of 101

Add comparison

Likelihood to Recommend

Apache Pig

- Custom load, store, filter functionalities are needed and writing Java map reduce code is not an option due susceptible to bugs.- Chain multiple MR jobs into one pig job.
No photo available

Databricks Unified Analytics Platform

  • DB generally fits 95% of what you need to do
  • Primarily the ability to transform data and or do ad-hoc DS work
No photo available

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

  • Long logics in Java? Apache Pig is a good alternative.
  • Has a lot of great features including table joins on many databases like DBMS, Hive, Spark-SQL etc.
  • Faster & easy development compared to regular map-reduce jobs.
Kartik Chavan profile photo
  • Extremely Flexible in Data Scenarios
  • Fantastic Performance
  • DB is always updating the system so we can have latest features.
No photo available

Cons

  • UDFS Python errors are not interpretable. Developer struggles for a very very long time if he/she gets these errors.
  • Being in early stage, it still has a small community for help in related matters.
  • It needs a lot of improvements yet. Only recently they added datetime module for time series, which is a very basic requirement.
Kartik Chavan profile photo
  • Better Localized Testing
  • When they were primarily OSS Spark; it was easier to test/manage releases versus the newer DB Runtime. Wish there was more configuration in Runtime less pick a version.
  • Graphing Support went non-existent; when it was one of their compelling general engine.
No photo available

Usability

Apache Pig10.0
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 Platform9.0
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
No photo available

Alternatives Considered

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
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

  • 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
  • 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