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Azure Data Factory vs Equalum comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
90
Ranking in other categories
Cloud Data Warehouse (3rd)
Equalum
Ranking in Data Integration
52nd
Average Rating
9.2
Reviews Sentiment
7.1
Number of Reviews
7
Ranking in other categories
Data Replication (16th), Cloud Data Integration (26th)
 

Mindshare comparison

As of February 2025, in the Data Integration category, the mindshare of Azure Data Factory is 10.1%, down from 12.9% compared to the previous year. The mindshare of Equalum is 0.1%, down from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
reviewer1525674 - PeerSpot reviewer
Frees staff to focus on data workflow and on what can be done with data, and away from the details of the technology
There are areas they can do better in, like most software companies that are still relatively young. They need to expand their capabilities in some of the targets, as well as source connectors, and native connectors for a number of large data sources and databases. That's a huge challenge for every company in this area, not just Equalum. If I had the wherewithal to create a tool that could allow for all that connectivity, it would be massive, out-of-the-box. There are all the updates every month. An open source changes constantly, so compatibility for these sources or targets is not easy. And a lot of targets are proprietary and they actually don't want you to connect with them in real time. They want to keep that connectivity for their own competitive tool. What happens is that a customer will say, "Okay, I've got Oracle, and I've got MariaDB, and I've got SQL Server over here, and I've got something else over there. And I want to aggregate that, and put it into Google Cloud Platform." Having connectors to all of those is extremely difficult, as is maintaining them. So there are major challenges to keeping connectivity to those data sources, especially at a CDC level, because you've got to maintain your connectors. And every change that's made with a new version that comes out means they've got to upgrade their version of the connector. It's a real challenge in the industry. But one good thing about Equalum is that they're up for the challenge. If there's a customer opportunity, they will develop and make sure that they update a connector to meet the needs of the customer. They'll also look at custom development of connectors, based on the customer opportunity. It's a work in progress. Everybody in the space is in the same boat. And it's not just ETL tools. It's everybody in the Big Data space. It's a challenge. The other area for improvement, for Equalum, is their documentation of the product. But that comes with being a certain size and having a marketing team of 30 or 40 people and growing as an organization. They're getting there and I believe they know what the deficiencies are. Maintaining and driving a channel business, like Equalum is doing, is really quite a different business model than the direct-sales model. It requires a tremendous amount of documentation, marketing information, and educational information. It's not easy.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"We have been using drivers to connect to various data sets and consume data."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."
"The most valuable features are data transformations."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"The main impact for Oracle LogMiner is the performance. Performance is drastically reduced if you use the solution’s Oracle Binary Log Parser. So, if we have 60 million records, initially it used to take a minute. Now, it takes a second to do synchronization from the source and target tables."
"I found two features in Equalum that I consider the most valuable. One is that Equalum is a no-code tool. You can do your activities on its graphical interface, which doesn't require complex knowledge of extracting, changing, or loading data. Another feature of Equalum that I like the most is that it monitors the data transfers and tells you if there's any issue so that you can quickly check and correct it. Equalum also tells you where the problem lies, for example, if it's a hardware or communication issue."
"Equalum has resulted in system performance improvements in our organization. Now, I am ingressing data off of multiple S3 sources, doing data processing, and formatting a schema. This would usually take me a couple of days, but now it takes me hours."
"It's got it all, from end-to-end. It's the glue. There are a lot of other products out there, good products, but there's always a little bit of something missing from the other products. Equalum did its research well and understood the requirements of large enterprise and governments in terms of one tool to rule them all, from a data migration integration perspective."
"It's a really powerful platform in terms of the combination of technologies they've developed and integrated together, out-of-the-box. The combination of Kafka and Spark is, we believe, quite unique, combined with CDC capabilities. And then, of course, there are the performance aspects. As an overall package, it's a very powerful data integration, migration, and replication tool."
"Equalum is real-time. If you are moving from an overnight process to a real-time process, there is always a difference in what reports and analytics show compared to what our operational system shows. Some of our organizations, especially finance, don't want those differences to be shown. Therefore, going to a real-time environment makes the data in one place match the data in another place. Data accuracy is almost instantaneous with this tool."
"All our architectural use cases are on a single platform, not multiple platforms. You don't have to dump into different modules because it is the same module everywhere."
"Equalum provides a single platform for core architectural use cases, including CDC replication, streaming ETL, and batch ETL. That is important to our clients because there is no other single-focus product that covers these areas in that much detail, and with this many features on the platform. The fact that they are single-minded and focused on CDC and ETL makes this such a rich solution. Other solutions cover these things a little bit in their multi-function products, but they don't go as deep."
 

Cons

"There's space for improvement in the development process of the data pipelines."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."
"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."
"Data Factory's performance during heavy data processing isn't great."
"Lacks in-built streaming data processing."
"There aren't many third-party extensions or plugins available in the solution."
"They need to expand their capabilities in some of the targets, as well as source connectors, and native connectors for a number of large data sources and databases. That's a huge challenge for every company in this area, not just Equalum."
"Their UI could use some work. Also, they could make it just a little faster to get around their user interface. It could be a bit more intuitive with things like keyboard shortcuts."
"The deployment of their flows needs improvement. It doesn't work with a typical Git branching and CI/CD deployment strategy."
"If you need to use the basic features of Equalum, for example, you don't even need data integration, then many competitors in the market can give you basic features. For instance, if you need batch ETL, you can pick among solutions in the market that have been around longer than Equalum. What needs improvement in Equalum is replication, as it could be faster. Equalum also needs better integration with specific databases such as Oracle and Microsoft SQL Server."
"I should be able to see only my project versus somebody else's garbage. That is something that would be good in future. Right now, the security is by tenants, but I would like to have it by project, e.g., this project has this source and flows in these streams, and I have access to this on this site."
"There is not enough proven integration with other vendors. That is what needs to be worked on. Equalum hasn't tested anything between vendors, which worries our clients. We need more proven vendor integration. It is an expensive product and it needs to support a multi-vendor approach."
"Right now, they have a good notification system, but it is in bulk. For example, if I have five projects running and I put a notification, the notification comes back to me for all five projects. I would like the notification to come back only for one project."
 

Pricing and Cost Advice

"Pricing appears to be reasonable in my opinion."
"This is a cost-effective solution."
"The pricing is a bit on the higher end."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"I would not say that this product is overly expensive."
"The solution is cheap."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"Understanding the pricing model for Data Factory is quite complex."
"As soon as you have more than six users, Equalum is lower in cost [than Talend] and if the group gets bigger, it's quite a big delta. If more users want to use it, you don't end up with an increase in licensing costs, so that makes it very easy. And if you need more licenses or more sources, it's a very simple upgrade methodology."
"Equalum is rather expensive compared to its competitors. So, you have to make up that cost in time savings, and we usually do that. If we are saving money, it is because we are reducing our development time."
"Equalum licensing costs vary, but I won't be able to give information on its fees."
"They have a very simple approach to licensing. They don't get tied up with different types of connectivity to different databases. If you need more connectors or if you need more CPU, you just add on. It's component-based pricing."
"Equalum was reasonably priced. It is not like those million dollar tools, such as Informatica."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Manufacturing Company
23%
Computer Software Company
16%
Financial Services Firm
10%
Insurance Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
Why should I use Equalum instead of LogMiner?
You'd want to use the Equalium Oracle Binary Log Parser because it's just better than the LogMiner. Sure, LogMiner is made by Oracle and probably the team knows some insight to make it efficient th...
Is Equalum compatible with all databases?
I'm using Equalum's data replication software for Oracle because that's the one database it's designed for. While it may sound limiting, when you find out how many solutions it can provide for you ...
Can I use Equalum for free?
No, it's not free but you can benefit from a free trial, though. There's an option to try their platform for a limited amount of time, so that may be useful to help you decide if you want to contin...
 

Overview

 

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
SIEMENS, GSK, Wal-Mart, T Systems
Find out what your peers are saying about Azure Data Factory vs. Equalum and other solutions. Updated: January 2025.
838,713 professionals have used our research since 2012.