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Matillion

Matillion

Overview

What is Matillion?

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.

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Learn from top reviewers

Matillion review

Rating: 7 out of 10
May 13, 2025
IncentivizedVetted ReviewVerified User
Matillion ETL is being used by our datamanagement team for the ingestion of data from our organisation into the datawarehouse in Snowflake and for transforming this data throu...
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Verified user
Team Lead
Matillion3 years of experience

My Honest Opinion on Matillion ETL.

Rating: 9 out of 10
May 2, 2025
IncentivizedVetted ReviewVerified User
We use Matillion for a lot of data jobs and schedules as data engineers. Most of the stuff is where we are loading our production tables in our data warehouse based on Redshif...
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Verified user
Engineer
Matillion1 year of experience

Matillion - What's in the Bag?

Rating: 8 out of 10
March 17, 2025
IncentivizedVetted ReviewVerified User
Matillion is the primary ETL tool in our business. We use it daily to build data pipelines for facilitating client dashboards which are hosted in our online platform.
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Steve Bramblet
Engineer - Engineering
Senior Data Specialist
Lime Intelligence
Matillion3 years of experience

My experiences using Matillion

Rating: 9 out of 10
January 10, 2025
IncentivizedVetted ReviewVerified User
We totally rebuilt our legacy data warehouse software and built a datalake in Matillion using Snowflake as a database. Before that we used Informatica Powercenter on premise. ...
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Verified user
Engineer
Matillion2 years of experience

Matillion is perfect for fast, scalable ETL

Rating: 9 out of 10
January 2, 2025
IncentivizedVetted ReviewVerified User
We use our own AWS instance to run Matillion ETL, and it has made our lives infinitely easier. Bringing in new data is a breeze, as well as setting up increasingly complex dat...
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Verified user
Engineer
Matillion3 years of experience
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How Matillion Differs From Its Competitors

Time to Value

We switched to Matillion shortly after I began working at my current role. It probably took a week to get up and running? For moderately experienced engineers they can build / maintain existing pipelines with a couple days tooling around to get familiar.
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Time to Value

It was all about understanding the philosophy of the tool. I only had some introduction course given by Matillion (a few hours). After that it was easy to start building solutions following our requirements. I think I needed only a few months to completely build our Datalake solution. For our …
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Time to Value

It took us approximately 2 months to develop our data flows. The migration process from existing flows proved to be challenging and time-consuming due to the complexity of our workflows. Although building proof of concepts (POCs) was a quick and easy task, the transition to a production …
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Time to Value

The most difficult challenge that we faced was working with our legal team to ensure that data was protected and that nothing important was exposed. Within a week, we were able to get Matillion setup, installed and functioning in basic mode. Whenever we bring in new data sources, it may be …
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Time to Value

Within a month of getting Matillion we had an established pipeline that was extracting data from the company's application database and updating the corresponding data in the warehouse. Additional data source (e.g. Salesforce and Netsuite) were quick to implement (c. 2 weeks per data source) …
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Time Saved

Yes we did. It was possible to update the data warehouse database every 3-4 hours instead of every 24 hours. In addition, and perhaps more importantly, it provided a more stable ETL process. The previous one was prone to breaking/failing and Matillion provided a more reliable process and one that …
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Cost Savings

In terms of infrastructure costs, our costs have gone up using Matillion. Historically we used AWS DMS to clone the production database into a Postgres database. This old process, however, was prone to issues and failures, e.g. when the production database was updated with new column(s)/table(s) …
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Business Outcomes

We were able to connect to our main data sources using Matillion (a MySQL database, Salesforce and Netsuite). Other data sources, that are API based and didn't have specific components in Matiilion were more of a challenge at the time. Although API functionality has been improved since we …
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Onboarding

Onboarding was quick and relatively pain free. The team did have experience using Matillion prior to implementation which obviously helped. However, once the server was setup with the appropriate security groups to access data sources, building the Matillion jobs was straight forward and the UI …
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Time to Value

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 …
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Time to Value

Our initial build was METL (older version of Matillion). This meant we had to create an EC2 instance on AWS. This initial setup took maybe a few days. but once we spun up the mahine and got it all working, we connected Matillion to our data warehouse in a matter of minutes. The new DPC Matillion …
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Time to Value

At the beginning of the ETL CDC process, it took us several working sessions with the teams to get all of the different components constructed in AWS, and then to find out it didn't meet our needs was a bit disappointing. With the CDC in Data Loader, though, we were up and running in a couple of …
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Time Saved

Yes, we went from saving files locally to in our Snowflake cloud warehouse. That gain is unmeasurable, but if I had to put a number on it I would say a full 24 hour increase at least. Matillion made reporting not only faster, but possible at all.
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Time to Value

If you have some experience with ETL development, you can understand Matillion jobs logic easily even without reading a lot of documentation. My adaptation period was about one week. For example, after one week, I was able to create some iteration objects and use Grid variables as well.
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Time to Value

Matillion is pretty intuitive if someone is already familiar with data pipeline concepts. My onboarding lasted a few days, and I was able to be productive with bug fixes and improvements on existing pipelines in a week or so. Designing and building a new pipeline is also very easy and quick, but …
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Time to Value

Learning curve is steep but fair.
Once understood what the tool has been designed for and how much it relies on the target DWH (being a ELT more than a ETL) things get easier.

Moving data from a simple db to the DWH could be achieved in a few days of learning, starting to add some logic or …
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Time to Value

It took us around one week to understand the tool. The primary time was spent understanding how to configure variables and connect to different sources. Creating a reusable template and then using it in other workflows is initially a bit complex. In a week, we became more comfortable with the …
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Time to Value

We were able to get up and running with Matillion remarkably quickly, we were able to get some test flows up in a few hours and a more in depth setup took about one day, including configuring the software and connecting to our data sources. Within the first week, we configured our full ETL …
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Time to Value

After running a POC of the tool for a month and a half, my team decided to move forward with a contract. The implementation part was pretty quick and well handled by Matillion implementation team. After a few weeks we were able to have a few pipelines running daily and feeding our datawarehouse.
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Time to Value

It took just a few hours to get set up with Matillion. Only in cases where we had to connect to data sources, in some cases, it took time as third parties had to white-list the IP address for Matillion to allow the connection. Overall setting up the instance, and setting up environment variables …
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Time to Value

I have installed Matillion from the start. To deploy it in Google platform it took me 2 weeks of time as I was very new to the tool. Once the instance is available, to create project, GCP credentials and GIT setup, it may take a day. Finally creating a sample pipeline and to test it will be a …
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Time to Value

I managed to install into Azure in a single day.

I watched a few YouTube videos (which I would like to see more of) and managed to create less complex ELT transfers in a single day.

Snowflake connection was a little more complex than it could be....and variable handling takes a while to grasp …
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

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Pricing

View all pricing

Developer: For Individuals

$2.50/credit

Cloud
Pay as you go per user

Basic

$1000

Cloud
per month 500 prepaid credits (additional credits: $2.18/credit)

Advanced

$2000

Cloud
per month 750 prepaid credits (additional credits: $2.73/credit)

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttps://www.matillion.com/pricing

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
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Features

Data Source Connection

Ability to connect to multiple data sources

7.8
Avg 8.4

Data Transformations

Data transformations include calculations, search and replace, data normalization and data parsing

7
Avg 8.2

Data Modeling

A data model is a diagram or flowchart that illustrates the relationships between data

7.5
Avg 7.9

Data Governance

Data governance is the practise of implementing policies defining effective use of an organization's data assets

8.2
Avg 8.2
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Product Details

What is Matillion?

Matillion is a data integration platform that can be used by data teams to build and manage pipelines for AI and analytics - at scale.

Matillion enables data teams and data professionals to take advantage of their data, AI and the cloud to build valuable data assets that can be used across a wide variety of applications from analytics to AI use cases.


Matillion boasts users among enterprises including Cisco, London Stock Exchange Group, EDF and Slack, who use Matillion for use cases from insights and operational analytics, to data science, machine learning and AI.

Matillion Features

Data Source Connection Features

  • Supported: Connect to traditional data sources
  • Supported: Connecto to Big Data and NoSQL

Data Transformations Features

  • Supported: Simple transformations
  • Supported: Complex transformations

Data Modeling Features

  • Supported: Business rules and workflow
  • Supported: Collaboration
  • Supported: Testing and debugging

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.

Matillion Integrations

Matillion Competitors

Matillion Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo
Supported CountriesGlobal
Supported LanguagesEnglish

Frequently Asked Questions

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.

Talend Data Integration, Informatica Intelligent Data Management Cloud, and Fivetran are common alternatives for Matillion.

Reviewers rate Data model creation and Metadata management highest, with a score of 9.1.

The most common users of Matillion are from Mid-sized Companies (51-1,000 employees).
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Reviews From Top Reviewers

View all reviews
(1-5 of 137)

My Honest Opinion on Matillion ETL.

Rating: 9 out of 10
Incentivized
May 02, 2025
Verified User
Engineer in Information Technology
Consumer Goods Company, 51-200 employees
Vetted Review
Verified User
Matillion
1 year of experience
Use Cases and Deployment Scope
We use Matillion for a lot of data jobs and schedules as data engineers. Most of the stuff is where we are loading our production tables in our data warehouse based on Redshift. Staging data from different APIs, so a lot of Python components and SQL components. Now we have started using shared jobs, so a lot of repetitive stuff is done in shared jobs. We try to have fewer schedules. We also try to schedule stuff in our main data pipelines, such as every hour, week, month, and day.

Matillion is perfect for fast, scalable ETL

Rating: 9 out of 10
Incentivized
January 02, 2025
Verified User
Engineer in Information Technology
Marketing & Advertising Company, 201-500 employees
Vetted Review
Verified User
Matillion
3 years of experience
Use Cases and Deployment Scope
We use our own AWS instance to run Matillion ETL, and it has made our lives infinitely easier. Bringing in new data is a breeze, as well as setting up increasingly complex data pipeline tasks. From our oldest SQL servers long overdue to be retired to the latest APIs, it takes minutes to stage new data, and it makes tricky problems easy. Hard to imagine a world where we didn't have Matillion.

Matillion review

Rating: 7 out of 10
Incentivized
May 13, 2025
Verified User
Team Lead in Other
Non-profit Organization Management Company, 501-1000 employees
Vetted Review
Verified User
Matillion
3 years of experience
Use Cases and Deployment Scope
Matillion ETL is being used by our datamanagement team for the ingestion of data from our organisation into the datawarehouse in Snowflake and for transforming this data through the datawarehouse to the accès layers for our end users

My experiences using Matillion

Rating: 9 out of 10
Incentivized
January 10, 2025
Verified User
Engineer in Information Technology
Entertainment Company, 1001-5000 employees
Vetted Review
Verified User
Matillion
2 years of experience
Use Cases and Deployment Scope
We totally rebuilt our legacy data warehouse software and built a datalake in Matillion using Snowflake as a database. Before that we used Informatica PowerCenter on premise. Although Informatica also offered a cloud solution (IICS) which offered more flexibility, we switched to Matillion because it met all our wishes to set up a metadata-driven data warehouse. Iterating through (meta) data in Matillion is very simple and the results can be used as variables in almost all Matillion components. So if the data definitions of our sources change we only have to change metadata and almost never software anymore. There are also components available that can read metadata from out source systems, so if a column in a table in the source system is added then it also automatically added to our datalake and data warehouse
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