in my opinion, Meh
We are moving away from Matillion to MWAA Airflow with dbt.
Maintaining source control in github is important to us.
We have used Matillion …
Maintaining source control in github is important to us.
We have used 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…
Recent Reviews
How Matillion Differs From Its Competitors
Awards
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Popular Features
- Simple transformations (124)8.181%
- Connect to traditional data sources (122)7.777%
- Complex transformations (123)6.464%
- Testing and debugging (109)5.555%
Reviewer Pros & Cons
Pricing
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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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Product Details
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- Competitors
- Tech Details
- FAQs
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
Matillion Integrations
Matillion Competitors
Matillion Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
| Supported Countries | Global |
| Supported Languages | English |
Frequently Asked Questions
Talend Data Integration, Informatica Intelligent Cloud Integration Services, 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).
Comparisons
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Reviews and Ratings
(204)Attribute Ratings
Reviews
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March 18, 2023
Matillion for driving Data Mesh
- Push down code to Snowflake
- Supports many transformations
- Scalable platform
- Git integration
- Customer engagement
- Matillion as SaaS
- Documentation needs to be improved
- Some of the functionalities like support for many aws SQS
March 14, 2023
Matillion - Robust ETL tool
- Connectors for multiple systems/applications spread across Databases, APIs, Files, etc.
- The concept of Shared jobs for reusability
- Seamless integration with Multiple Cloud providers
- UI Feature to track job changes
- Option to put the comments while importing/exporting the jobs
- Option to search for component names inside the opened job in canvas
March 11, 2023
The Joy of data transformation!
- Reliability
- Seamless integration with Snowflake.
- Customer support and engagement.
- Better integration with large enterprise applications. Ie. Salesforce, Anaplan, etc.
March 08, 2023
Matillion... Right tool for the right time.
- speed of data movement
- ease of use with python
- great integration into our cloud stack
- documentation
- production support
- rsd and api integration components
March 08, 2023
Low Code and Python component review
- Excellent support team
- Consistent releases with great documentation
- UI is easy to learn and navigate
- Job scheduling is straightforward
- I like the environment variables and how you can export a variable to a shared job
- I think a non-CLI approach to installing and uninstalling python libraries would be nice. I mean, it isn't difficult to install a python library via Linux or CLI, but I imagine most companies don't feel comfortable allowing Matillion users to go on a virtual server and installing it themselves. Requirement.txt file for installing libraries would be simple, and maybe that could also be used to uninstall libraries as well......or maybe the library gets automatically downloaded if it is imported into a python script but the library doesn't exist.
- Python Component is lacking very much in terms of UI. It would be unrealistic for me to suggest Matillion build its own EDI, but it would be nice if a python component could connect to a local IDE. Right now, if you want to write any decent length python code, you are going to be stuck copying and pasting your code from your local IDE.
- It is also very difficult to debug in Matillion because you can't set breakpoints. Local IDE integration can resolve that.
- I would like to have more templates to copy from for certain simplistic scenarios. For instance, a template for a job that fails which sends an AWS SNS with the Job name, component it failed on, and the error message. It wasn't as simple as I thought it would be to figure out and having to use a shared job for such circumstances can be painful because you have to export a bunch of variables.
- There should be a drop down list for Global Matillion variables as it is difficult to remember at times.
March 08, 2023
Matillion - easy to use ETL tool
- Integrate with AWS, GCP Microsoft Azure
- work with data from multiple sources
- user friendly
- sometime slow to load
- documentation can be difficult to navigate
- update is sometime difficult on infra
March 08, 2023
Matillion easy and faster
- Excellent tool to do ELT data pipeline using Snowflake
- Easy graphical orchestration to enable complex dependencies
- Easy manage users and group permissions
- Easy to schedule jobs using time dependency and job dependency
- Provides many API's to fetch data from multiple vendors
- Though its not a Matillion use case, but Matillion can add more machine learning and Data science capabilities,
- easy AWS services integration
- More sofisticated Data Lineage graph
September 21, 2022
Matillion, a nice ETL tool.
- I is really simple and good.
- Documentation
- Drags and Drops.
- Performance
- I think the price could be a bit cheaper.
September 02, 2022
Matillion a great, easy to implement resource
- Run stored procedures on AWS Postgres RDS instances
- Sync data from diverse data sources including production databases and APIs to Redshift data warehouse
- Version updates often are not backward compatible. As a result updating to a new version requires a huge LOE.
June 09, 2022
Matillion review
- Easy integration with AWS Redshift and Snowflake.
- Pay for what you use.
- Ease of service.
- Constant Java heap space errors because of hard limits on EC2 instance hosting.
- It is expensive considering the infrastructure cost is added to Redshift costs.
- Matillion does not scale well. It has a hard limit on the hardware / EC2 instances it can use.
- Push down query performance with Snowflake.
- The ability to hit any API using Python.
- A robust offering of pre-built connectors to databases, APIs, and other SaaS vendors.
- No user community site for experienced developers to share their patterns and help grow the dev community
- Documentation can get stale or be changed without notice.
- Several aspects of the product are not user-friendly, and if implemented by an experienced product/UX person it would make the product easily 2x to 3x better.
- No ability to vote on what features are in the pipeline.
Score 10 out of 10
Vetted Review
Verified User
- Extremely user-friendly workflow orchestration between multiple languages such as SQL, Python, bash, and various API connectors
- Salesforce connectors to pull and push data between systems save us a ton of time
- Matillion Exchange workflows allow for easy sharing of templated best practice transformation jobs with ease
- Very responsive support
- GIT Functionality needs works, has unnecessary steps and needs "GIT DIFF"
- A cloud hosted version would help resolve a lot of issues
- Serverless solutions for scaling up storage and compute for certain jobs in Matillion if we wanted to run data science workflows
August 02, 2021
Data Integration and transformation platform
Score 9 out of 10
Vetted Review
Verified User
- Data integration and transformation.
- Saving data in the cloud for future referencing.
- The user interface can be simplified to enable users to learn the functionality curve within a short period of time.
July 09, 2021
Matillion Review
- It's easy to understand
- Support team
- Good performance
- The step of transformation is not 100% clear.
- The price could be better.
- Their forum is not that good.
July 08, 2021
Ease and complete tool, I would suggest it!
- Easy to use
- Flexible in the use of parameters.
- Well integrated with insertable Json code.
- Tables comparison automation works well.
- Pay for use
- It was difficult to understand how to use parameters.
- Job validation takes long when you run a job.
- Logging for debug is not always so clear.
- Matillion's UI makes it easier to understand the flow of data in your data pipeline.
- Custom Python scripts make it easier to manage and manipulate variables and also to create custom functions (e.g. we use one to post messages to Slack when jobs have failed/succeeded).
- Handling failures in processes is straightforward.
- Passing variables between jobs (orchestration or transformation) feels a bit clunky. It can also be frustrating that you can't pass a variable back up to the calling orchestration job, you can only pass it down to child jobs.
- It would be great to have some kind of debug mode, through which you're able to 'step through' the various tasks in an orchestration/transformation job.
- Matillion's generic API functionality is difficult to understand. Things like handling pagination and rate limiting are complex. Although I understand improvements have been made in recent versions.
July 01, 2021
Push the data with Matillion
Score 9 out of 10
Vetted Review
Verified User
- Just drag and drop, good to do.
- Very simple to use.
- Good features.
- Support responds a bit late.
June 30, 2021
Visual ELT at its best
- Breaks jobs down
- Graphics Interface
- Has lots of AWS documentation but not as much Azure.
June 29, 2021
Easy to implement and scale
- Automation and scheduling
- Security and authorization
- Ease of use
- API Calls using python
- More community support and forums
June 29, 2021
Matillion Review
- Supports a wide variety of digital platform connectors, which could be helpful for any industry working to automate any of their reporting needs.
- Support for AWS technologies adds to greater advantage.
- Takes up unique functionality provided by the database into account which is very helpful.
- Also provides direct SQL query feed-in option for any migration of existing solution.
- With the added functionality available in Matillion, the understanding to use complex features becomes challenging for a new development team.
- Updates are regularly provided by Matillion support team but then they fail to specify the release document, new features or updates carried out in each update.
- Validation failure in scheduled jobs is sometimes encountered without any reason or proper RCA.
- Complex user management flow.
January 05, 2021
ETL made easy for non-programmers
- Components available to do work with any source
- Ability to connect to sources without preconfigured component with extensability
- Able to kick off jobs from SNS, SQS
- There are so many options that the learning curve could be long for a newbie
- Can only parallelize the load in 16 partitions so it can't make use of parallelism of Redshift
- Menu items for admins may not always work and would have to resort to shell scripting (offered)
November 30, 2020
Ease of Use and Reusability for Excellent ROI
- It integrates well with Amazon Web Services, like S3 and Redshift
- It makes good use of Redshift to perform ETL quickly
- The ability to parameterize ETL jobs with variables makes it possible to get a lot of reuse from ETL jobs
- Integration with source control is a challenge; we had to roll our own solution to pull our Matillion jobs via its API into files we could add to source control
- It can be a challenge to avoid conflicts when multiple people are developing jobs in the same project
- It's only available on Redhat flavors of Linux (e.g. Amazon Linux, Redhat, CentOS)
November 27, 2020
Good at what it does.
- Easy to use GUI.
- Grid variables and other variables make it reusable.
- Task history helps us identify issues.
- Need source control for the ETL scripts.
- Need to undo features for mistakes.
November 25, 2020
Excellent AWS Data Integration Platform
- Easy to build data integration job
- compatible with AWS cloud platform
- lots of components for different use cases
- No powerful job monitor console
- Flexibility for supporting scripting languages
- Expensive license fees
October 06, 2020
Beautiful UI and UX to compete with any ETL, but at a cost!
- The easy-to-use GUI makes it easier for our team to pass on the knowledge and upskill engineers on our ETL processes.
- The feature set is rich with many options to allow us to try different ways to transform our data without having to code.
- Many different integration points allow us to plug straight into services like SQS to help us communicate with our own internal services.
- Matillion does not scale well. It has a hard limit on the hardware / EC2 instances it can use. Most of the time that does not provide enough parallel processing for the millions of records we want to transform.
- It is expensive considering the infrastructure cost is added to Redshift costs, so the overall value for analytics is something we are constantly challenging.
- Constant Java heap space errors, again this is because of hard limits on EC2 instance hosting.