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Matillion

Matillion

Overview

What is Matillion?

Matillion is a productivity platform for data teams.Matillion's Data Productivity Cloud helps data teams – coders and non-coders alike – to move, transform, and orchestrate data pipelines with the goal of empowering teams to deliver quality data at a speed…

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Recent Reviews

in my opinion, Meh

1 out of 10
March 29, 2024
Incentivized
We are moving away from Matillion to MWAA Airflow with dbt.
Maintaining source control in github is important to us.

We have used Matillion …
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Matillion - Decent

6 out of 10
March 19, 2024
Incentivized
We use Matillion to schedule and run our ETL jobs. This helps our company to have accurate and timely data in order to make data-driven …
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Matillion Review

8 out of 10
February 07, 2024
Incentivized
We use Matillion for loading data from various sources into Snowflake Data Lake. We have data in various source systems such as SQL …
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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

Popular Features

View all 11 features
  • Connect to traditional data sources (125)
    7.5
    75%
  • Simple transformations (127)
    6.7
    67%
  • Complex transformations (126)
    5.4
    54%
  • Testing and debugging (112)
    4.6
    46%

Reviewer Pros & Cons

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Pricing

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N/A
Unavailable

What is Matillion?

Matillion is a productivity platform for data teams. Matillion's Data Productivity Cloud helps data teams – coders and non-coders alike – to move, transform, and orchestrate data pipelines with the goal of empowering teams to deliver quality…

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

7.3
Avg 8.3

Data Transformations

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

6.1
Avg 8.2

Data Modeling

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

6.9
Avg 8.1

Data Governance

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

8.2
Avg 8.3
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Product Details

What is Matillion?

Matillion is a productivity platform for data teams.

Matillion's Data Productivity Cloud helps data teams – coders and non-coders alike – to move, transform, and orchestrate data pipelines with the goal of empowering teams to deliver quality data at a speed and scale that matches the business’s data ambitions.

The vendor states enterprises including Cisco, DocuSign, Pacific Life, Slack, and TUI use Matillion to move, transform, and orchestrate their data for a wide range of use cases from insights and operational analytics, to data science, machine learning, and AI.

Native integration with popular cloud data platforms such as Snowflake, Databricks, Amazon Redshift and Google BigQuery lets data teams at every skill level automate management, refinement, and data delivery for every data integration need.


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 Technical Details

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

Frequently Asked Questions

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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Comparisons

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Reviews and Ratings

(207)

Attribute Ratings

Reviews

(1-25 of 126)
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Score 8 out of 10
Vetted Review
Verified User
Incentivized
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.
Score 4 out of 10
Vetted Review
Verified User
Incentivized
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 maintaining it when it becomes complex is pretty complicated and requires much investigation work.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
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 transformation will take some months to master, including handling of variables and how they behave.

You will be tempted to use the python scripting component instead of the builtin components and it can be handy but also keeping you from using the full potential.

Some components, in order to remove the complexity of the task ended up being complex on their own. This layer means that you have to learn how the component works more than the source task challenges.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
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 matter of minutes
Score 7 out of 10
Vetted Review
Verified User
Incentivized
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 product.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
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 initially.
Callum O'Connor | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
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 is all SaaS so was a lot quicker to set up, maybe a few hours, a day max.
February 07, 2024

Matillion Review

Score 8 out of 10
Vetted Review
Verified User
Incentivized
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 was quite quick.
Matthew Belo | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
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 hours after getting everything built and permissions established. Much better product. With the direct-to-Snowflake version, a new version can be stood up and snapshotted in less than an hour.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
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 environment demanded a significant amount of time.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
IT took us a few weeks to get it deployed in a secure environment and get the Single Sign On working with it. After it was deployed correctly, it took no time at all to write the first transformation and get it scheduled. It is a very easy to use application.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Our POC with Matillion went well, everything we testing paid off dividends. From the POC we have moved quickly to implementation and are working with support specialists to make sure that we get full use of the product. Implementation timeline for us has been approximately 4 months, with one of the key parts being to get into SAP data.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We were able to implement Matillion for our development environment in about a weeks time. There was some learning involved but the application was implemented within a weeks time. It took us about 2 more weeks to build some standards around and understanding how to use Matillion as an enterprise wide tool for data transformations.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Its quite easy to learn Matillion and start implementing the use cases. we were able to implement medium level business use cases within 1 week with all complex logic and standard practices. The data were loaded in first run only with no errors and the time taken to load the data was also less.
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