30 Ratings
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Score 8.2 out of 100
80 Ratings
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Score 8.7 out of 100

Likelihood to Recommend

Databricks Lakehouse Platform

Databricks has helped my teams write PySpark and Spark SQL jobs and test them out before formally integrating them in Spark jobs. Through Databricks we can create parquet and JSON output files. Datamodelers and scientists who are not very good with coding can get good insight into the data using the notebooks that can be developed by the engineers.
Anonymous | TrustRadius Reviewer

Informatica PowerCenter

PowerCenter is well equipped to handle large amounts of data movement in an organization with many disparate sources and a structured development team. It excels in enforcing enterprise development standards through things like metadata manager and the monitoring capabilities (as well as being able to design monitoring rules for everything from naming standards to design practices). It is especially well suited at handling flat-file data in addition to its many connectors and native support for just about any ANSI standard database. For large development teams or the desire to remain flexible at an enterprise scale, Powercenter is a top-tier solution.For small projects or even smaller development teams with mostly a single data source, expect frustration with being able to quickly test a solution as the design flow is very structured. It is also designed in a way that segregation of duties at a very high level can also cause small development teams to be counter-productive. Each step in the design process is a separate application, and although stitched together, is not without its problems. In order to design a simple mapping for example, you would first need a connection established to the source (example, ODBC) and keep in mind that it will automatically name the container according to how you named your connection. You would then open the designer tool, import a connection as a source, optionally check it in, create a target, optionally check it in as well, and design a transformation mapping. In order to test or run it, you will need to open a separate application (Workflow Manager) and create a workflow from your mapping, then create a session for that workflow and a workflow for those one or more sessions at which point you can test it. After running it, in order to observe, you then need to open a separate application (Monitor) to see what it is doing and how well. For a developer coming from something like SSIS, this can be daunting and cumbersome for building a simple POC and trying to test it (although from the inverse, building an enterprise scalable ETL solution from SSIS is its own challenge).
Jody Gitchel | TrustRadius Reviewer

Feature Rating Comparison

Data Source Connection

Databricks Lakehouse Platform
Informatica PowerCenter
8.6
Connect to traditional data sources
Databricks Lakehouse Platform
Informatica PowerCenter
9.1
Connecto to Big Data and NoSQL
Databricks Lakehouse Platform
Informatica PowerCenter
8.2

Data Transformations

Databricks Lakehouse Platform
Informatica PowerCenter
8.7
Simple transformations
Databricks Lakehouse Platform
Informatica PowerCenter
9.3
Complex transformations
Databricks Lakehouse Platform
Informatica PowerCenter
8.0

Data Modeling

Databricks Lakehouse Platform
Informatica PowerCenter
7.7
Data model creation
Databricks Lakehouse Platform
Informatica PowerCenter
7.4
Metadata management
Databricks Lakehouse Platform
Informatica PowerCenter
8.3
Business rules and workflow
Databricks Lakehouse Platform
Informatica PowerCenter
8.3
Collaboration
Databricks Lakehouse Platform
Informatica PowerCenter
7.6
Testing and debugging
Databricks Lakehouse Platform
Informatica PowerCenter
7.5
feature 1
Databricks Lakehouse Platform
Informatica PowerCenter
7.0

Data Governance

Databricks Lakehouse Platform
Informatica PowerCenter
8.0
Integration with data quality tools
Databricks Lakehouse Platform
Informatica PowerCenter
7.9
Integration with MDM tools
Databricks Lakehouse Platform
Informatica PowerCenter
8.1

Pros

Databricks Lakehouse Platform

  • It supports all data science programming languages like Python and R
  • it takes very few minutes to deploy models into production
  • it has tools that ensures collaborations between developers
Kofi Joshua | TrustRadius Reviewer

Informatica PowerCenter

  • 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.
Anonymous | TrustRadius Reviewer

Cons

Databricks Lakehouse Platform

  • 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.
Anonymous | TrustRadius Reviewer

Informatica PowerCenter

  • One of the challenges of PowerCenter is the lack of integration between the components and functionality provided by PowerCenter. PowerCenter consists of multiple components such has the repository service, integration service, metadata service. Considerable time and resources were required to install and configure these components before PowerCenter was available for use.
  • In order to connect to various data sources such as Netezza database or SAS datasets, PowerCenter requires the installation and configuration of separate plug-ins. We spent considerable time trouble-shooting and debugging problems while trying to get the various plug-ins integrated with PowerCenter and get them up and running as described in the documentation.
  • PowerCenter works well with structured data. That is, it is easy to work with input and output data that is pre-defined, fixed, and unchanging. It is much more difficult to work with dynamic data in which new fields are added or removed ad-hoc or if data format changes during the data ingest process. We have not been as successful in using PowerCenter for dynamic data.
  • One of the challenges of learning PowerCenter is that it is difficult to find documentation or publications that help you learn the various details about PowerCenter software. Unlike SAS Institute, Informatica does not publish books about PowerCenter. The documentation available with PowerCenter is sparse; we have learned many aspects of this technology through trial and error.
Anonymous | TrustRadius Reviewer

Likelihood to Renew

Databricks Lakehouse Platform

No score
No answers yet
No answers on this topic

Informatica PowerCenter

Informatica PowerCenter 10.0
Based on 4 answers
Our team enjoys using Informatica and feels that it is one of the best ETL tools on the market.
Robert Goodman | TrustRadius Reviewer

Usability

Databricks Lakehouse Platform

Databricks Lakehouse Platform 9.0
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
Anonymous | TrustRadius Reviewer

Informatica PowerCenter

Informatica PowerCenter 9.1
Based on 3 answers
Positives;- Multi User Development Environment- Speed of transformation- Seamless integration between other Informatica products.Negatives;- There should be less windows to maintain developers' focus while using. You probably need 2 big monitors when you start development with Informatica Power Center.- Oracle Analytical functions should be natively used.- E-LT support as well as ETL support.
Gurcan Orhan | TrustRadius Reviewer

Performance

Databricks Lakehouse Platform

No score
No answers yet
No answers on this topic

Informatica PowerCenter

Informatica PowerCenter 9.6
Based on 3 answers
PowerCenter is robust and fast, and it does a great job meeting all the needs, not just the most commercially vocal needs. In the hands of an expert power user, you can accomplish almost anything with your data. It is not for new users or intermittent users-- for that the Cloud version is a better fit. Be prepared for costly connectors (priced differently for each source or destination you are working with), and just be planful of your projects so you are not paying for connectors you no longer need or want
Anonymous | TrustRadius Reviewer

Support Rating

Databricks Lakehouse Platform

No score
No answers yet
No answers on this topic

Informatica PowerCenter

Informatica PowerCenter 8.7
Based on 2 answers
Informatica power center is a leader of the pack of ETL tools and has some great abilities that make it stand out from other ETL tools. It has been a great partner to its clients over a long time so it's definitely dependable. With all the great things about Informatica, it has a bit of tech burden that should be addressed to make it more nimble, reduce the learning curve for new developers, provide better connectivity with visualization tools.
Anonymous | TrustRadius Reviewer

Alternatives Considered

Databricks Lakehouse Platform

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 | TrustRadius Reviewer

Informatica PowerCenter

PowerCenter is the industry leader when it comes to interfacing with multiple source and target systems. The graphical interface increases employee productivity while reducing human resource expenditures and training requirements. These other tools offer some similar capabilities, but lack the range and depth when compared with the PowerCenter platform.
Brian Randolph | TrustRadius Reviewer

Return on Investment

Databricks Lakehouse Platform

  • Rapid growth of analytics within our company.
  • Cost model aligns with usage allowing us to make a reasonable initial investment and scale the cost as we realize the value.
  • Platform is easy to learn and Databricks provides excellent support and training.
  • Platform does not require a large DevOPs investment
Anonymous | TrustRadius Reviewer

Informatica PowerCenter

  • Positive - Easy to maintain processes built in Informatica Power Center.
  • Positive - Rapidly build and deploy ETL data mappings.
  • Positive - Develop the overall workflow process to run all ETL processes for the project.
  • Negative - Informatica Power Center can be a bit expensive, so your application needs to warrant the enterprise support.
Anonymous | TrustRadius Reviewer

Pricing Details

Databricks Lakehouse Platform

General

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

Databricks Lakehouse Platform Editions & Modules

Edition
Standard$0.071
Premium$0.101
Enterprise$0.131
  1. Per DBU
Additional Pricing Details

Informatica PowerCenter

General

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

Informatica PowerCenter Editions & Modules

Additional Pricing Details

Rating Summary

Likelihood to Recommend

Databricks Lakehouse Platform
8.0
Informatica PowerCenter
8.8

Likelihood to Renew

Databricks Lakehouse Platform
Informatica PowerCenter
10.0

Usability

Databricks Lakehouse Platform
9.0
Informatica PowerCenter
9.1

Performance

Databricks Lakehouse Platform
Informatica PowerCenter
9.6

Support Rating

Databricks Lakehouse Platform
Informatica PowerCenter
8.7

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