Apache Pig vs Db2 Big SQL

Likelihood to Recommend

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

Read full review

Kartik Chavan

Data Analyst

The University of Texas at ArlingtonElectrical/Electronic Manufacturing, 1001-5000 employees

View all 5 answers on this topic

My recommendation obviously would depend on the application. But I think given the right requirements, IBM DB2 Big SQL is definitely a contender for a database platform. Especially when disparate data and multiple data stores are involved. I like the fact I can use the product to federate my data and make it look like it's all in one place. The engine is high performance and if you desire to use Hadoop, this could be your platform.

Read full review

Gene Baker

Vice President, Chief Architect, Development Manager and Software Engineer

WySTAR Global Retirement Solutions, a Wells Fargo CompanyFinancial Services, 10,001+ employees

View all 2 answers on this topic

Pros

Iterative Development - you can write aliases/variables, which are not immediately executed and these are stored in a DAG, which is only evaluated upon dumping or storing another alias.
Fast execution - Works with MapReduce, Tez, or Spark execution frameworks to provide fast run times at large scales.
Local and remote interoperability - Scripts that depend on testing a small dataset locally before moving to the full thing can simply be done with "pig -x local."

Read full review

Jordan Moore

Software Consultant

Avalon ConsultingInformation Technology and Services, 51-200 employees

View all 5 answers on this topic

data storage
data manipulation
data definitions
data reliability

Read full review

John Spies

Database Administrator

RewardsLive.comInternet, 51-200 employees

View all 2 answers on this topic

Cons

May not fit every need and a SQL-like abstraction may be more effective for some tasks (look at Spark-SQL, Hive, or even an actual DBMS)
All Pig jobs are written in a Domain Specific Language so not a lot of transferable knowledge
Writing your own User Defined Functions (UDFS) is a nice feature but can be painful to implement in practice

Read full review

Verified User

Engineer in Engineering

Computer Software Company, 51-200 employees

View all 5 answers on this topic

Cloud readiness.
Ease of implementation.

Read full review

Gene Baker

Vice President, Chief Architect, Development Manager and Software Engineer

WySTAR Global Retirement Solutions, a Wells Fargo CompanyFinancial Services, 10,001+ employees

View all 2 answers on this topic

Usability

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.

Read full review

Subhadipto Poddar

Research Assistant

Iowa State UniversityHigher Education, 5001-10,000 employees

View all 1 answers on this topic

Db2 Big SQL 8.0

Based on 1 answer

IBM DB2 is a solid service but hasn't seen much innovation over the past decade. It gets the job done and supports our IT operations across digital so it is fair.

Read full review

John Spies

Database Administrator

RewardsLive.comInternet, 51-200 employees

View all 1 answers on this topic

Support Rating

Apache Pig 6.0

Based on 2 answers

The documentation is adequate. I'm not sure how large of an external community there is for support.

Read full review

Jordan Moore

Software Consultant

Avalon ConsultingInformation Technology and Services, 51-200 employees

View all 2 answers on this topic

Db2 Big SQL 8.7

Based on 2 answers

IBM did a good job of supporting us during our evaluation and proof of concept. They were able to provide all necessary guidance, answer questions, help us architect it, etc. We were pleased with the support provided by the vendor. I will caveat and say this support was all before the sale, however, we have a ton of IBM products and they provide the same high level of support for all of them. I didn't see this being any different. I give IBM support two thumbs up!

Read full review

Gene Baker

Vice President, Chief Architect, Development Manager and Software Engineer

WySTAR Global Retirement Solutions, a Wells Fargo CompanyFinancial Services, 10,001+ employees

View all 2 answers on this topic

Alternatives Considered

- Provided better ways for optimized hadoop jobs than Hive but not anymore.- Spark DSL is much more advanced and compute times are significantly less.

Read full review

Verified User

Team Lead in Engineering

Retail Company, 10,001+ employees

View all 5 answers on this topic

MS SQL Server was ruled out given we didn't feel we could collapse environments. We thought of MS-SQL as more of a one for one replacement for Sybase ASE, i.e., server for server. SAP HANA was evaluated and given a big thumbs up but was rejected because the SQL would have to be rewritten at the time (now they have an accelerator so you don't have to). Also, there was a very low adoption rate within the enterprise. IBM DB2 Big SQL was not selected even though technically it achieved high scores, because we could not find readily available talent and low adoption rate within the enterprise (basically no adoption at the time). We ended up selecting Exadata because of the high adoption rate within the enterprise even though technically HANA and Big SQL were superior in our evaluations.

Read full review

Gene Baker

Vice President, Chief Architect, Development Manager and Software Engineer

WySTAR Global Retirement Solutions, a Wells Fargo CompanyFinancial Services, 10,001+ employees

View all 2 answers on this topic

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.

Read full review

Kartik Chavan

Data Analyst

The University of Texas at ArlingtonElectrical/Electronic Manufacturing, 1001-5000 employees

View all 5 answers on this topic

better data visibility
solid reliability for mission critical data

Read full review

John Spies

Database Administrator

RewardsLive.comInternet, 51-200 employees

View all 2 answers on this topic

Pricing Details

General

Free Trial

—

Free/Freemium Version

—

Premium Consulting/Integration Services

—

Entry-level set up fee?

No

General

Free Trial

—

Free/Freemium Version

—

Premium Consulting/Integration Services

—

Entry-level set up fee?

No

Apache Pig

Db2 Big SQL

Likelihood to Recommend

Apache Pig

Db2 Big SQL

Pros

Apache Pig

Db2 Big SQL

Cons

Apache Pig

Db2 Big SQL

Usability

Apache Pig

Db2 Big SQL

Support Rating

Apache Pig

Db2 Big SQL

Alternatives Considered

Apache Pig

Db2 Big SQL

Return on Investment

Apache Pig

Db2 Big SQL

Pricing Details

General

Free Trial

Free/Freemium Version

Premium Consulting/Integration Services

Entry-level set up fee?

General

Free Trial

Free/Freemium Version

Premium Consulting/Integration Services

Entry-level set up fee?

Add comparison