

Informatica PowerCenter and Databricks are major players in the data integration and machine learning sectors. Informatica PowerCenter is preferred for enterprise-level data integration projects due to its robust features in security, scalability, and transformation support, whereas Databricks holds the advantage in big data processing and machine learning, praised for its ease in interactive querying and collaboration.
Features: Informatica PowerCenter provides comprehensive data integration features, handling complex transformations, data across platforms, and efficient error handling. Databricks excels with its notebook interface, flexibility in using SQL, Python, and R, and collaboration tools, making it ideal for data science tasks.
Room for Improvement: Informatica PowerCenter's GUI is outdated, and its version control could be clearer. Users find its setup complex and costly. Databricks could enhance its pricing model, expand its library for predictive analysis, and improve BI tool integration. More tutorials for beginners and better documentation are also needed.
Ease of Deployment and Customer Service: Informatica PowerCenter's on-premises setup is noted for complexity and often requires professional help, though technical support is effective despite inconsistent feedback. Databricks, being cloud-based, allows for flexible deployment with lower initial setup complexity. It is praised for problem resolution but some criticize the cost of premium services.
Pricing and ROI: Informatica PowerCenter is known for its high cost, with a pricing model based on CPU and data sources, making it a choice for large enterprises. Databricks offers a competitive pay-per-use model, appreciated for scalability and flexibility, though it can become costly with extensive use. Databricks is recognized for delivering significant ROI in data science projects.
For a lot of different tasks, including machine learning, it is a nice solution.
When it comes to big data processing, I prefer Databricks over other solutions.
It also plays a vital role in revenue calculations, net asset valuations, and other key factors that support customer data and investment data pipelines.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
I rate the technical support as fine because they have levels of technical support available, especially partners who get really good support from Databricks on new features.
I like the technical support provided by Informatica.
I have occasionally needed to communicate with the technical support of Informatica PowerCenter, especially when raising cases for complex mappings and performance optimization to identify bottlenecks in transformations.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is an easily scalable platform.
I would rate the scalability of this solution as very high, about nine out of ten.
In the cloud, scaling up and down becomes easy when working with cloud providers.
For scalability, I would rate Informatica PowerCenter between eight to nine.
They release patches that sometimes break our code.
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
Databricks is definitely a very stable product and reliable.
Informatica PowerCenter is stable and can scale well.
The product is very stable with very few issues encountered in production.
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
With Informatica PowerCenter, I am looking for an AI interface that looks at the underlying data model of the databases and the metadata of the tables, allowing the developer to provide instructions on what data sources to connect to and how to apply or create Transformations.
Utilizing more stored procedures from Oracle databases in an easy way would significantly boost performance.
Informatica Cloud and its support becomes quite expensive for the organization compared to peers such as SnapLogic or Netezza, which offer lower pricing.
It is not a cheap solution.
I find that the pricing and licensing for Informatica PowerCenter align with its quality.
The price of Informatica PowerCenter is high, especially for small and medium-sized businesses.
Databricks' capability to process data in parallel enhances data processing speed.
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
The system supports real-time integration, which is essential for many of my tasks.
The functions in Informatica PowerCenter that I have found most valuable are the way it manages the volume of data, the push down optimization, and the performance aspects of it, mostly related to parallelism techniques.
The most valuable features of Informatica PowerCenter that I have found so far include transformations, the ease of connectivity with different source systems, and the parameter files.
| Product | Market Share (%) |
|---|---|
| Databricks | 9.2% |
| Snowflake | 16.1% |
| Teradata | 8.5% |
| Other | 66.2% |
| Product | Market Share (%) |
|---|---|
| Informatica PowerCenter | 3.7% |
| SSIS | 4.0% |
| Informatica Intelligent Data Management Cloud (IDMC) | 3.7% |
| Other | 88.6% |


| Company Size | Count |
|---|---|
| Small Business | 25 |
| Midsize Enterprise | 12 |
| Large Enterprise | 56 |
| Company Size | Count |
|---|---|
| Small Business | 15 |
| Midsize Enterprise | 10 |
| Large Enterprise | 72 |
Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.
Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.
What features make Databricks unique?
What benefits can users expect from Databricks?
In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.
Informatica PowerCenter is a data integration and data visualization tool. The solution works as an enterprise data integration platform that helps organizations access, transform, and integrate data from various systems. The product is designed to support companies in the full cycle of a project, from its initial rollout to critical deployments. Informatica PowerCenter allows developers and analysts to collaborate while accelerating the work process to deploy projects within days instead of months.
The Advanced edition of the product provides an additional real-time engine which allows companies to have always-on enterprise data integration. This ensures seamless collaboration and increment of data lineage visibility and impacts analysis.
The Premium edition of the solution offers an early warning system that detects unexpected behaviors or incorrect utilization of resources in the workflows and alerts companies in the case that these occur. This version of the product also offers automatic data validation, which ensures data accuracy and reduces testing time and expenditure of resources for by up to 90%.
Informatica PowerCenter Features
The product provides users with various features which allow them to execute data integration initiatives such as analytics, data warehousing, data governance, consolidation, and application migration. The features of the solution include:
Informatica PowerCenter Benefits
The benefits of using Informatica PowerCenter include:
Reviews from Real Users
Yahya T., a developer and architect at L'Oreal, says the product is stable, provides good support, and integrating it with other systems is very fast.
Mohamed E., a senior manager for Data management and data governance at a tech company, says PowerCenter is stable, mature, and offers flexibility in building the pipeline and has a drag-and-drop mode because it's GUI-based; technical support is brilliant.
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