IBM DataStage vs. Matillion

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM DataStage
Score 7.6 out of 10
N/A
IBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.N/A
Matillion
Score 8.0 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 DataStageMatillion
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
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Offerings
Pricing Offerings
IBM DataStageMatillion
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsBilled directly via cloud marketplace on an hourly basis, with annual subscriptions available depending on the customer's cloud data warehouse provider.
More Pricing Information
Community Pulse
IBM DataStageMatillion
Features
IBM DataStageMatillion
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
IBM DataStage
9.5
Ratings
12% above category average
Matillion
8.4
Ratings
0% above category average
Connect to traditional data sources10.00 Ratings8.80 Ratings
Connecto to Big Data and NoSQL9.00 Ratings8.00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
IBM DataStage
8.0
Ratings
2% below category average
Matillion
7.0
Ratings
15% below category average
Simple transformations8.00 Ratings7.50 Ratings
Complex transformations8.00 Ratings6.40 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
IBM DataStage
6.3
Ratings
23% below category average
Matillion
8.3
Ratings
4% above category average
Data model creation5.00 Ratings9.10 Ratings
Metadata management5.00 Ratings9.10 Ratings
Business rules and workflow6.00 Ratings8.30 Ratings
Collaboration6.00 Ratings7.40 Ratings
Testing and debugging6.00 Ratings7.60 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
IBM DataStage
6.0
Ratings
30% below category average
Matillion
8.2
Ratings
1% above category average
Integration with data quality tools6.00 Ratings8.20 Ratings
Integration with MDM tools6.00 Ratings8.20 Ratings
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User Ratings
IBM DataStageMatillion
Likelihood to Recommend
8.0
(0 ratings)
7.9
(0 ratings)
Likelihood to Renew
-
(0 ratings)
8.6
(0 ratings)
Usability
8.0
(0 ratings)
7.1
(0 ratings)
Performance
9.0
(0 ratings)
-
(0 ratings)
Support Rating
9.6
(0 ratings)
7.4
(0 ratings)
Implementation Rating
-
(0 ratings)
8.2
(0 ratings)
Product Scalability
-
(0 ratings)
7.4
(0 ratings)
Vendor post-sale
-
(0 ratings)
9.1
(0 ratings)
Vendor pre-sale
-
(0 ratings)
9.1
(0 ratings)
User Testimonials
IBM DataStageMatillion
Likelihood to Recommend
Excellent Cloud data mapping tool and easy creating multiple project data analytics in real-time and the report distribution are excellent via this IBM product. Easy tool to provide data visualization and the integration is effective and helpful to migrating huge amounts of data across other platforms and different websites insights gathering.
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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.
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Pros
  • Very reliable in handling data extraction, data transformation and loading
  • Flexibility in connecting to different type of databases, relational or non-relational
  • Great features such as parallel processing, hash handling, etc.
  • You can also take advantage of its FTP functions, and scheduling features if you need to.
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  • The user interface of your data pipelines makes it easier for people who aren’t as techy as data engineers to observe what's going on.
  • Customer support is quick, not always as efficient as you would want it to be, but still.
  • Nice documentation available.
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Cons
  • You must understand and know the algorithms, since the wrong use of them generates more time in processing.
  • Metadata. You need to develop with connectors, and taking all the Metadata from the menu, all the data that you complete manually, you can't track it.
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  • 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.
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Likelihood to Renew
No answers on this topic
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.
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Usability
Because it is a flexible tool that can manage many flows and create a strong solution with a interesting use of variables. Easy to scale up as you can copy jobs arleady build and modify them. SQL queries allow to be fast in development and have the pushdown feature, but you loose a little of user friendly look. Metadata management is not strong as a visual feature, but can be determine by job codes.
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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.
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Performance
It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
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No answers on this topic
Support Rating
IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.
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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.
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Implementation Rating
No answers on this topic
We were able to control on access and built various enviroment for implementation
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Alternatives Considered
No, it wasn’t my decision to use such an ETL product. I’m just the administrator at this point. I’ve heard there are other products there that are even on cloud support. That is much easier to use, more agile, and user-friendly. That doesn’t have that barrier from user to administrator to the developer standpoint.
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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.
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Scalability
No answers on this topic
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.
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Return on Investment
  • Not directly related to ROI or cost figures. Only comment here is that IBM tools tend to be more costly than average ETL tools, but it depends on if the company is an IBM shop.
  • One positive aspect is the company has had not a need to switch ETL tool for years.
  • Upgrading to newer versions of the tool brings flexibility in the tool and up-to-date features in relation to other applications.
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  • 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.
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ScreenShots

Matillion Screenshots

Screenshot of Matillion's GUI, used to orchestrate jobs with control data flow functionality, automating the ETL process.Screenshot of where structured and semi-structured data can be prepared to create clean data sets that can be used with any BI/reporting/visualization tool of choice. Matillion reads and combines data across a target warehouse external storage, such as S3 or Blob.Screenshot of Matillion's self-validating components, sample and row counts. If a job does fail, the warehouse queue services available with Matillion can be used get an alert to a connected email or Slack account.Screenshot of the SQL component used to run custom scripts from within Matillion. With hundreds of pre-built connectors out of the box, Matillion can handle complex transformation needs.