Azure Databricks vs. Informatica Cloud Data Quality

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Databricks
Score 8.7 out of 10
N/A
Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…N/A
Informatica Cloud Data Quality
Score 6.0 out of 10
N/A
The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.N/A
Pricing
Azure DatabricksInformatica Cloud Data Quality
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure DatabricksInformatica Cloud Data Quality
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Azure DatabricksInformatica Cloud Data Quality
Features
Azure DatabricksInformatica Cloud Data Quality
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
8.1
Ratings
3% below category average
Informatica Cloud Data Quality
-
Ratings
Connect to Multiple Data Sources6.20 Ratings00 Ratings
Extend Existing Data Sources9.00 Ratings00 Ratings
Automatic Data Format Detection9.00 Ratings00 Ratings
MDM Integration8.00 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
6.4
Ratings
27% below category average
Informatica Cloud Data Quality
-
Ratings
Visualization5.90 Ratings00 Ratings
Interactive Data Analysis6.90 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.0
Ratings
2% below category average
Informatica Cloud Data Quality
-
Ratings
Interactive Data Cleaning and Enrichment7.00 Ratings00 Ratings
Data Transformations9.00 Ratings00 Ratings
Data Encryption9.00 Ratings00 Ratings
Built-in Processors7.10 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
8.3
Ratings
1% below category average
Informatica Cloud Data Quality
-
Ratings
Multiple Model Development Languages and Tools8.10 Ratings00 Ratings
Automated Machine Learning9.00 Ratings00 Ratings
Single platform for multiple model development8.00 Ratings00 Ratings
Self-Service Model Delivery8.00 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Azure Databricks
8.5
Ratings
0% below category average
Informatica Cloud Data Quality
-
Ratings
Flexible Model Publishing Options8.00 Ratings00 Ratings
Security, Governance, and Cost Controls9.00 Ratings00 Ratings
Data Quality
Comparison of Data Quality features of Product A and Product B
Azure Databricks
-
Ratings
Informatica Cloud Data Quality
8.9
Ratings
2% above category average
Data source connectivity00 Ratings9.30 Ratings
Data profiling00 Ratings9.20 Ratings
Master data management (MDM) integration00 Ratings8.90 Ratings
Data element standardization00 Ratings8.20 Ratings
Match and merge00 Ratings8.70 Ratings
Address verification00 Ratings9.00 Ratings
Best Alternatives
Azure DatabricksInformatica Cloud Data Quality
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Score 9.4 out of 10
HubSpot Data Hub
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Score 7.8 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
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User Ratings
Azure DatabricksInformatica Cloud Data Quality
Likelihood to Recommend
9.8
(0 ratings)
9.2
(0 ratings)
Likelihood to Renew
-
(0 ratings)
6.6
(0 ratings)
Usability
8.0
(0 ratings)
8.0
(0 ratings)
Availability
-
(0 ratings)
9.0
(0 ratings)
Performance
-
(0 ratings)
9.0
(0 ratings)
Online Training
-
(0 ratings)
10.0
(0 ratings)
Implementation Rating
-
(0 ratings)
10.0
(0 ratings)
Product Scalability
-
(0 ratings)
9.0
(0 ratings)
User Testimonials
Azure DatabricksInformatica Cloud Data Quality
Likelihood to Recommend
Having access to all databases and tables in one place is what has helped me and my team to function better. The in built functionality/access to SQL and Python is definitely an added bonus! The icing on the cake is the ability to export your data into an Excel spreadsheet for additional analysis. If you have less to no working knowledge of SQL or Python, its better to look at alternatives.
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We used Informatica Data Quality to measure the "Data Quality Score" of internal and external reports at my company. Business users set up data profiling and prepared detailed analysis documents for business analysts. and developers developed Data Quality Mapplets for other IT teams to import their Informatica Power Center repositories. Results are stored in a centralized data quality space and then reported and summarized to related business users in detailed ways. At the end of each project, we are now able to place a "Data Quality Score" watermark score on each report involved.
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Pros
  • Consistently great performance when dealing with huge scale data with the help of spark architecture
  • Magic commands such as spark sql, pyspark, scala . This comes really handy in day to day work
  • Integration with other Azure services is super smooth and robust
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  • Watch the data real time- After creating the job the data quality engine checks and run the custom rules creating a navigation window at the bottom for review and accessing the data right away.
  • Character Set Mapping
  • Makes sense of our own data, which in turn gives us confidence that we can provide to the end users. IDQ helped us with erroneous data in accounting and HR for accurate and immaculate reports
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Cons
  • Intuitive interface
  • Ease of use
  • Providing FAQ or QRGs
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  • Several partnerships diminishing the value of technologies
  • Unable to get list of objects from Repository (like sources & targets) that don't have any dependency
  • Scheduling: The built-in scheduling tool has many constraints such as handling Unix/VB scripts etc. Most enterprises use third party tools for this.
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Likelihood to Renew
No answers on this topic
I gave a rating of 8 due to the fact that we use Informatica for both our data quality product and ETL product. Having both integrated makes it so much easier. Microsoft had a similar product of finding duplicates, but at the time it didn't seem mature enough. The usability also in IDQ was pretty easy to navigate and use.
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Usability
Based on my extensive use of Azure Databricks for the past 3.5 years, it has evolved into a beautiful amalgamation of all the data domains and needs. From a data analyst, to a data engineer, to a data scientist, it jas got them all! Being language agnostic and focused on easy to use UI based control, it is a dream to use for every Data related personnel across all experience levels!
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Easy to use not only for developers but also business users
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Reliability and Availability
No answers on this topic
The application works well except an occasional error out while using the system. It usually gets fixed when restarting the Infa server
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Performance
No answers on this topic
Performance works just fine. It was able to load 200+ business terms, 150+ DQ automation, etc. very well.
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Alternatives Considered
Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse platform also fares better than it counterparts of Iceberg implementation or a loosely bound Delta Lake implementation of Synapse
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Informatica Data Quality has a wide range of cleansing features, that are detailed, professional, and accurate in scaling down the required database. Further, Informatica Data Quality ensures there is proper collaboration, and this fosters businesses to have the freedom of working closely with several programs. Finally, Informatica Data Quality design is authentic and allows personalization.
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Scalability
No answers on this topic
Scalability works as expected and it is truly an enterprise system.
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Return on Investment
  • The support team is amazing, they help you at every stage of the projects, from sales to delivery.
  • On a framework level, it has had an amazing impact and has reduced the clients overall data platform costs by a staggering 65%
  • There has been a 40% Manual work requirement on average for the clients when they move to Azure Databricks Data Platform
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  • Integration with tools like PowerCenter helped faster delivery of product, and at the same time conversion
  • Reduce overall project cost due to bad data , bad quality, exceptions identified nearing go-live and post production
  • Employee efficiency is increased exponentially due to more automated, customized tool
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ScreenShots