Datameer vs Informatica PowerCenter

• It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT.
• It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization .
• Excel feature is awesome for business users which is already provided by Datameer.
• Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation.
• Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash.
• It can be used in premise or in a cloud computing environment.
• Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem.

Read full review

• Informatica has a wide range of support for databases. Pretty much every mainstream DBMS is compatible here.
• Designing ETL mappings and workflows is a very intuitive process, and takes minimal learning time and effort even for a beginner.
• Informatica's biggest strength is its sheer performance. It is unmatched in terms of handling large volumes of data.

Read full review

• Many tabs sometimes reduce your focus
• Might be better to have a more compact design
• Video tutorials are a little long

Read full review

• There are too many ways to perform the same or similar functions which in turn makes it challenging to trace what a workflow is doing and at which point (ex. sessions can be designed as static or re-usable and the override can occur at the session or workflow, or both which can be counter productive and confusing when troubleshooting).
• The power in structured design is a double edged sword. Simple tasks for a POC can become cumbersome. Ex. if you want to move some data to test a process, you first have to create your sources by importing them which means an ODBC connection or similar will need to be configured, you in turn have to develop your targets and all of the essential building blocks before being able to begin actual development. While I am on sources and targets, I think of a table definition as just that and find it counter intuitive to have to design a table as both a source and target and manage them as different objects. It would be more intuitive to have a table definition and its source/target properties defined by where you drag and drop it in the mapping.
• There are no checkpoints or data viewer type functions without designing an entire mapping and workflow. If you would like to simply run a job up to a point and check the throughput, an entire mapping needs to be completed and you would workaround this by creating a flat file target.

Read full review

• Datameer definitely helped to increase employee efficiency, provide quick results for our data analytic teams.
• Quick data injection and data partitions allowed quick data scans.
• Integration with the Java sdk allowed us to reuse existing Java code.

Read full review

• The data pipeline automation capability of Informatica means that few resources are needed to pre-process the data that ultimately resides in a Data Warehouse. Once a workflow is implemented, manual intervention is not needed.
• PowerCenter did require more resources and time for installation and configuration than was expected/planned for.
• The lack of or minimal support of unstructured data means that newer sources of dynamic/changing data cannot be easily processed/transformed through PowerCenter workflows.

Read full review