103 Ratings
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Score 8.5 out of 101
46 Ratings
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Score 8.2 out of 101

Add comparison

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.
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Informatica Enterprise Data Integration

We are considering their PowerCenter Advanced version which will add metadata and business glossary capabilities.
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Feature Rating Comparison

Data Source Connection

Apache Spark
Informatica Enterprise Data Integration
9.5
Connect to traditional data sources
Apache Spark
Informatica Enterprise Data Integration
10.0
Connecto to Big Data and NoSQL
Apache Spark
Informatica Enterprise Data Integration
9.0

Data Transformations

Apache Spark
Informatica Enterprise Data Integration
9.5
Simple transformations
Apache Spark
Informatica Enterprise Data Integration
10.0
Complex transformations
Apache Spark
Informatica Enterprise Data Integration
9.0

Data Modeling

Apache Spark
Informatica Enterprise Data Integration
8.1
Data model creation
Apache Spark
Informatica Enterprise Data Integration
8.5
Metadata management
Apache Spark
Informatica Enterprise Data Integration
8.8
Business rules and workflow
Apache Spark
Informatica Enterprise Data Integration
7.6
Collaboration
Apache Spark
Informatica Enterprise Data Integration
7.5
Testing and debugging
Apache Spark
Informatica Enterprise Data Integration
8.1

Data Governance

Apache Spark
Informatica Enterprise Data Integration
8.0
Integration with data quality tools
Apache Spark
Informatica Enterprise Data Integration
8.2
Integration with MDM tools
Apache Spark
Informatica Enterprise Data Integration
7.8

Pros

  • Apache Spark makes processing very large data sets possible. It handles these data sets in a fairly quick manner.
  • Apache Spark does a fairly good job implementing machine learning models for larger data sets.
  • Apache Spark seems to be a rapidly advancing software, with the new features making the software ever more straight-forward to use.
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  • Shared objects allow transformations, sources, and targets to be reused.
  • Mapplets allow for blocks of transformations to be reused.
  • Field by field transformations.
  • Union and join a variety of data sources.
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Cons

  • could do a better job for analytics dashboards to provide insights on a data stream and hence not have to rely on data visualization tools along with spark
  • also there is room for improvement in the area of data discovery
Shiv Shivakumar profile photo
  • The Informatica web service interface can be improved from a performance point of view and also from a troubleshooting point of view.
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Likelihood to Renew

No score
No answers yet
No answers on this topic
Informatica Enterprise Data Integration8.9
Based on 3 answers
Availability of options to integrate with application oriented databases like SAP, Salesforce etc.Product Support.Reliability.
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Alternatives Considered

We evaluated SAS alongside with Apache Spark but during the course of proof of concept found that Apache Spark was able to support the hadoop eco-system and hadoop file system much better. It was much faster at that time while having the ability to process data quickly for the business analytical needs and and also scaled up well.
Shiv Shivakumar profile photo
I've really only used Informatica as an ETL developer
Brandon Fitzpatrick profile photo

Return on Investment

  • It has had a very positive impact, as it helps reduce the data processing time and thus helps us achieve our goals much faster.
  • Being easy to use, it allows us to adapt to the tool much faster than with others, which in turn allows us to access various data sources such as Hadoop, Apache Mesos, Kubernetes, independently or in the cloud. This makes it very useful.
  • It was very easy for me to use Apache Spark and learn it since I come from a background of Java and SQL, and it shares those basic principles and uses a very similar logic.
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  • Informatica allows us to achieve complex data integration among our systems and into our data warehouse environment. Without this tool in place, hours of manual manipulation would occur to integrate this data and extract it into the appropriate DW solution.
Robert Goodman profile photo

Pricing Details

Apache Spark

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

Informatica Enterprise Data Integration

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
Additional Pricing Details