IBM’s App Connect is a cloud-based data integration platform with data mapping and transformation capabilities within connectors between high-volume systems. App Connect also offers near-real time data synchronization and an API builder that is adaptable to the user’s coding skill level.
N/A
Matillion
Score 7.9 out of 10
N/A
Matillion is a data pipeline platform used to build and manage pipelines. Matillion empowers data teams with no-code and AI capabilities to be more productive, integrating data wherever it lives and delivering data that’s ready for AI and analytics.
$2.50
Pay as you go per user
Pricing
IBM App Connect
Matillion
Editions & Modules
No answers on this topic
Developer: For Individuals
$2.50/credit
Pay as you go per user
Basic
$1000
per month 500 prepaid credits (additional credits: $2.18/credit)
Advanced
$2000
per month 750 prepaid credits (additional credits: $2.73/credit)
Enterprise
Request a Quote
Offerings
Pricing Offerings
IBM App Connect
Matillion
Free Trial
Yes
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Billed directly via cloud marketplace on an hourly basis, with annual subscriptions available depending on the customer's cloud data warehouse provider.
IBM App Connect started as MQSeries Integrator (MQSI) more than 20 years ago. In the IT environment, this is like an eternity. And this allowed a lot of customer experience and needs to be embedded in the product. Without it becoming a legacy application. The changes done in …
I used the IBM WebSphere DataStage tool which is an ETL tool where we extract transform and load. This tool is a little tougher to understand than App Connect. For example, to build a job in App Connect is easier than DataStage. We can schedule the job to run in the same …
IBM API Connect is positioned ahead of Apigee in the Gartner report. But in my opinion the development experience and the data transformation capability is way better in Apigee and it’s a proved solution and has a huge client list. (I have worked on an American Express …
We did not select Cast Iron as our iPaaS solution, it was the weakest competitor in the field that we evaluated. Our experience was that it was not nearly as easy to learn, without in-depth training and guidance, and the developer UI was extremely buggy. We subjected each of …
WebSphereCast Iron is preferred for our sales and delivery teams over Informatica. We find the products and teams for WebSphere Cast Iron easier to work with here and find WebSphere Cast Iron better when integrating with non-Salesforce systems. WebSphere Cast Iron struggles to …
We selected IBM App Connect Enterprise due to our confidence in IBM as a long-term partner and our history with their integration technology (Message Broker/Bus). IBM App Connect provides the robustness and high reliability needed for our core on-premises systems, with proven …
The choice of IBM App Connect was a strategic decision driven by the urgent need for agile, user-friendly, and cost-effective application and data integration. While DataPower, webMethods, and API Connect are powerful tools in their own rights, their primary focuses as security …
Matillion is cheaper and we really like the customer support of Matillion as well as lerning materials provided by Matillion were far better. They also made connectors for us for free while others were charging us for it.
Matillion gives great ability to connect to variety of sources and bring data into cloud data warehouse using connector based approach with which we can build complex transformation jobs which can do automated data fetches from your sources.
Matillion has better capabilities and better built-in elements that saves your time and efforts. also the connectivity across multiple data warehousing tool is better in Matillion. even the performance of the pipeline and the time required to create a particular pipeline is …
My manager selected Million based on his previous work experience. He believes it is easy to use and maintain, cheaper than competitors, and suitable for our use case.
The only other ETL tool I've used was SSIS. At first I thought Matillion seemed "kiddish" after using the polished Microsoft tool but now I think Matillion is easier and can do much more as it has so many built-in connectors etc. We selected Matillion at our job because of …
n/a -- joined the team after they already were established in Matillion. Have had brief looks at other ETL products but found nothing compelling enough to suggest a change.
We selected Matillion primarily because of it's ability to connect to numerous data sources and easily create transformation jobs. While FiveTran does a better job managing and examining deltas, it is not easy to use and is very non user friendly. SSIS was not a good fit for …
Fivetran offers a managed service and pre-configured schemas/models for data loading, which means much less administrative work for initial setup and ongoing maintenance. But it comes at a much higher price tag. So, knowing where your sweet spot is in the build vs. buy spectrum …
We decided to move forward with Matillion because it was the best tool among tools that support both ingesting data from a source system to a target database and running transformation workflows on it afterwards. Fivetran and Airbyte only support data ingestion and we had our …
Cost and ease of use were better for our purposes. Matillion distinguishes itself from Fivetran and Snaplogic through its user-friendly design, no-code interface, in-depth transformation capabilities, allowing for complex data manipulations directly within the platform, …
The Matillion selection was not my decision. But I think it's a good enough choice. It is especially valuable that the team can learn Matillion easily and that the project can be understood by the entire team with the visual environment instead of complex ETLs.
Both the Databricks platform and Dbt Cloud are more powerful from the point of view of the development lifecycle and data use cases covered. They are also more complex and require specialized data engineering skills to be used. Matillion has a lower barrier of entry for small …
Removes most of the complexity around setting up and preparing things. If you could describe with words what needs to be done to move data from A to B, the implementation in Matillion would probably be the most similar in terms of simplicity of understanding what you are doing …
Matillion is a good tool for integrating multiple clouds. Informatica has been a market standard for many years, it provides multiple capabilities for data governance, data quality, etc. However, Informatica is pretty expensive compared to Matillion. Also, Matillion is more …
IBM App Connect is well-suited to serve as a central integration hub, particularly for scenarios involving data transformation, complex routing logic, and dynamic backend routing. It excels at enabling legacy system modernization and supports real-time, event-driven architectures effectively. However, it is less appropriate for simple point-to-point integrations or for use cases requiring workflow process management and human task orchestration, where BPM or lightweight automation tools may be more suitable.
Great: Need to query simpler APIs, or utilize well known services such as GSheets etc.? Matillion has got some of the best and easiest to use connectors out there. Not so great: Do you need have a competent CI/CD flow that you will be able to update / compare from Matillion as well as other sources at the same time? Good luck, you will need to be extra careful, as you might have to have a deeper dive into your servers Terminal each time you have a git conflict.
Static and monolithic, it will show its limits when running multiple concurrent jobs.
Github and versioning implementation is messy and broken. Don't use it.
There's not way to see/query the system resources, just wait for a server to crash due to out of memory. An admin panel would be appreciated + some env variables with updated info.
API implementation is cumbersome and limited.
There's no concept of hub and worker engine, everything happens of the same server (designing workflows and executing them). Having separate light ETL engines to run job could be better. (sort of docker/kubernetes/lambda functions).
Handling of variables is limited especially for returned values from sub components.
Some components could return more metadata at the end of their execution instead of the standard one.
Billing is badly designed not taking into account that the server is hosted by the client. Expensive.
We had several issue with migration where starting a new instance was required and then migrating the content. It was painful and time consuming also have to deal with support and engineering team on Matillion side.
CDC doesn't work as expected or it is not a mature product yet.
It is the best on-premise application to cloud integration in the market. I guess IBM is planning to integrate IBM App Connect with the IBM API Connect solution.
Matillion is easy to use and flexible to debug. Performance are good and support is giving us a good service level. There are still some technical points to be developed more (such as SAP extraction). but easy flows are really fast to be developed. We are also using a tool for migration from other tools, and it is useful as Matillion is producing XML code.
You can do some really powerful things with this system. The overall design is an attempt to make configurable some of the routine tasks/common functionality, but allow for development/customization of the core of the application.
Easy tasks are really easy, and complex tasks are still possible. With prior knowledge of general data warehousing principles and experience with other data transformation tools, it's straightforward to get familiar with and use Matillion. I initially used minimal external support from a partner for some more complex tasks but very soon could work entirely independently with Matillion.
Overall, I've found Matillion to be responsive and considerate. I feel like they value us as a customer even when I know they have customers who spend more on the product than we do. That speaks to a motive higher than money. They want to make a good product and a good experience for their customers. If I have any complaint, it's that support sometimes feels community-oriented. It isn't always immediately clear to me that my support requests are going to a support engineer and not to the community at large. Usually, though, after a bit of conversation, it's clear that Matillion is watching and responding. And responses are generally quick in coming.
We selected IBM App Connect Enterprise due to our confidence in IBM as a long-term partner and our history with their integration technology (Message Broker/Bus). IBM App Connect provides the robustness and high reliability needed for our core on-premises systems, with proven scalability to the cloud. Its key strength is enabling deep integration by combining low-code with the power of complex, custom logic, ensuring the platform's capabilities exactly matched our need to handle complex flows.
We selected Matillion primarily because of it's ability to connect to numerous data sources and easily create transformation jobs. While Fivetran does a better job managing and examining deltas, it is not easy to use and is very non user friendly. SSIS was not a good fit for our team and required a significant amount of attention and server management that we did not want to invest in.
We're using Matillion on EC2 instances, and we have about 20 projects for our clients in the same instance. Sometimes, we're struggling to manage schedules for all projects because thread management is not visible, and we can't see the process at the instance level.
Time savings -- we could custom code nearly everything Matillion does, but it would take days/weeks instead of minutes/hours.
There's a bit of a learning curve to truly unlock Matillion's potential, and that can be frustrating for some new users, but once you get over that curve, the possibilities are endless.
It allows us to centralize the hundreds of way to bring data in, so that even if you have to troubleshoot what someone else wrote, it's easy to jump in and understand what is happening.
