What users are saying about
145 Ratings
8 Ratings
145 Ratings
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Score 8.8 out of 100
8 Ratings
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Score 8.4 out of 100

Attribute Ratings

  • Apache Spark is rated higher in 2 areas: Likelihood to Recommend, Usability
  • IBM Db2 Big SQL is rated higher in 1 area: Support Rating

Likelihood to Recommend

9.2

Apache Spark

92%
22 Ratings
9.0

Db2 Big SQL

90%
2 Ratings

Likelihood to Renew

10.0

Apache Spark

100%
1 Rating

Db2 Big SQL

N/A
0 Ratings

Usability

9.4

Apache Spark

94%
2 Ratings
8.0

Db2 Big SQL

80%
1 Rating

Support Rating

8.7

Apache Spark

87%
6 Ratings
8.8

Db2 Big SQL

88%
4 Ratings

Likelihood to Recommend

Apache Spark

The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.
Thomas Young | TrustRadius Reviewer

Db2 Big SQL

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.
Gene Baker | TrustRadius Reviewer

Pros

Apache Spark

  • Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
  • Faster in execution times compare to Hadoop and PIG Latin
  • Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
  • Interoperability between SQL and Scala / Python style of munging data
Nitin Pasumarthy | TrustRadius Reviewer

Db2 Big SQL

  • data storage
  • data manipulation
  • data definitions
  • data reliability
John Spies | TrustRadius Reviewer

Cons

Apache Spark

  • Memory management. Very weak on that.
  • PySpark not as robust as scala with spark.
  • spark master HA is needed. Not as HA as it should be.
  • Locality should not be a necessity, but does help improvement. But would prefer no locality
Anson Abraham | TrustRadius Reviewer

Db2 Big SQL

  • Cloud readiness.
  • Ease of implementation.
Gene Baker | TrustRadius Reviewer

Pricing Details

Apache Spark

General

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

Starting Price

Db2 Big SQL

General

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

Starting Price

Likelihood to Renew

Apache Spark

Apache Spark 10.0
Based on 1 answer
Capacity of computing data in cluster and fast speed.
Steven Li | TrustRadius Reviewer

Db2 Big SQL

No score
No answers yet
No answers on this topic

Usability

Apache Spark

Apache Spark 9.4
Based on 2 answers
The only thing I dislike about spark's usability is the learning curve, there are many actions and transformations, however, its wide-range of uses for ETL processing, facility to integrate and it's multi-language support make this library a powerhouse for your data science solutions. It has especially aided us with its lightning-fast processing times.
Anonymous | TrustRadius Reviewer

Db2 Big SQL

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.
John Spies | TrustRadius Reviewer

Support Rating

Apache Spark

Apache Spark 8.7
Based on 6 answers
1. It integrates very well with scala or python.2. It's very easy to understand SQL interoperability.3. Apache is way faster than the other competitive technologies.4. The support from the Apache community is very huge for Spark.5. Execution times are faster as compared to others.6. There are a large number of forums available for Apache Spark.7. The code availability for Apache Spark is simpler and easy to gain access to.8. Many organizations use Apache Spark, so many solutions are available for existing applications.
Yogesh Mhasde | TrustRadius Reviewer

Db2 Big SQL

Db2 Big SQL 8.8
Based on 4 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!
Gene Baker | TrustRadius Reviewer

Alternatives Considered

Apache Spark

Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.
Anonymous | TrustRadius Reviewer

Db2 Big SQL

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.
Gene Baker | TrustRadius Reviewer

Return on Investment

Apache Spark

  • Business leaders are able to take data driven decisions
  • Business users are able access to data in near real time now . Before using spark, they had to wait for at least 24 hours for data to be available
  • Business is able come up with new product ideas
Surendranatha Reddy Chappidi | TrustRadius Reviewer

Db2 Big SQL

  • better data visibility
  • solid reliability for mission critical data
John Spies | TrustRadius Reviewer

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