We performed a comparison between Databricks and Informatica PowerCenter based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: PeerSpot users consistently feel Databricks is a more complete solution, providing better integrations, features, and ease of use. The cloud-based architecture makes scaling seamless.
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"I like cloud scalability and data access for any type of user."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"The integration with Python and the notebooks really helps."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"It's very simple to use Databricks Apache Spark."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"Technical support is great. It's one of the reasons we really like them. When you compare support from IBM and support from Informatica, Informatica is much better."
"It is very comprehensive in terms of connector and transformation capabilities from both a source and target perspective."
"The features I find most valuable is that the solution is very user-friendly and the graphical design is very easy to understand."
"It's a very powerful tool you can use to load data, get data, do the drawing between the tables, and put into the packet in a very fast way."
"The most valuable feature is the new Data Lake feature, which provides the basic capabilities needed."
"It's a complete package, which is why we use this solution."
"If the systems get migrated or upgraded, the amount of resources required are very minimal. We can change the connections and establish a new connection. It's very helpful."
"Informatica PowerCenter has been implementing mapping design, data flow, and workflow execution for years."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
"Anyone who doesn't know SQL may find the product difficult to work with."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"There is room for improvement in visualization."
"The pricing of Databricks could be cheaper."
"The integration features could be more interesting, more involved."
"I believe that this product could be improved by becoming more user-friendly."
"As a connector to big data, it is not well developed. We've had problems connecting Informatica with Hadoop. The functionality to connect Informatica with Hadoop, for me it's not good."
"While on-premises is a better product, we really need to move to the cloud and need the cloud to be as robust as this product."
"We need another tool for monitoring. It would be easier if all the features were consolidated into one tool."
"PowerCenter could integrate better with cloud applications. We had to do a lot of configuration work using API integrations to connect with cloud applications. Informatica Cloud Data Integration has a generic connector that you can use directly, so it's much easier."
"Integrated Reporting service should be more smoothly transitioned from view to function to be in sync with the main design."
"This solution needs the functionality to do batch processing of data. It also lacks connectivity to NoSQL, unstructured data sources."
"PowerCenter could be improved by having more big data components. Normally, we prefer Informatica as a relational database, but nowadays, companies are trying to understand and use big data components. I think it would be useful if we had more chances to create a hub ecosystem because customers try to use some data integration tasks by SQL, Spark and Spark codes, and Scala, but at the end of the day, the company will understand that we need to trace all the steps. An ETL tool is a must for that company, if we're talking about the regulated industries like finance, telcos, etc. If Informatica's biggest ecosystems feature were okay, I would prefer to use it."
"Its licensing can be improved. It should be features-wise and not bundle-wise. A bundle will definitely be costly. In addition, we might use one or two features. That's why the pricing model should be based on the features. The model should be flexible enough based on the features. Their support should also be more responsive to premium customers."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Informatica PowerCenter is ranked 3rd in Data Integration with 78 reviews. Databricks is rated 8.2, while Informatica PowerCenter is rated 8.0. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of Informatica PowerCenter writes "Stable, provides good support, and integrating it with other systems is very fast, but its pricing is expensive". Databricks is most compared with Amazon SageMaker, Dataiku, Dremio, Microsoft Azure Machine Learning Studio and Azure Stream Analytics, whereas Informatica PowerCenter is most compared with Informatica Cloud Data Integration, Azure Data Factory, SSIS, AWS Glue and Oracle Data Integrator (ODI). See our Databricks vs. Informatica PowerCenter report.
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