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…
Small team supported by Matillion
in my opinion, Meh
Maintaining source control in github is important to us.
We have used Matillion …
Experience the ETL with Matillion
Matillion for cloud data integration.
Matillion enables us to manage all ETL/ELT processes without any dedicated data engineering resources.
Matillion - Decent
Matillion- Simple and Easy Cloud ETL Solution for Snowflake Data Warehouse
Matilion helped grow my business
Low-code solution to transforming data at the speed of thought
All That You Need in Your Daily ETL Work
Matillion Review
Replication with Matillion Saves Time
Use Matillion - Become the no code superman
How Matillion Differs From Its Competitors
Time to Value
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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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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Time Saved
Cost Savings
Business Outcomes
Onboarding
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Training on Matillion and getting the development team on-board was quite a challenge. Would require immense experience to explore the core functionality of Matillion. Matillion was running …
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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
- Simple transformations (125)7.878%
- Connect to traditional data sources (123)7.474%
- Complex transformations (124)6.363%
- Testing and debugging (110)4.747%
Reviewer Pros & Cons
Pricing
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
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
- 7.4Connect to traditional data sources(123) Ratings
Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications
- 7.1Connecto to Big Data and NoSQL(83) Ratings
Ability to connect to non-traditional data sources like Hadoop and other big data technologies, and NoSQL databases
Data Transformations
Data transformations include calculations, search and replace, data normalization and data parsing
- 7.8Simple transformations(125) Ratings
Simple data transformations are calculations, data type conversions, aggregations and search and replace operations
- 6.3Complex transformations(124) Ratings
Complex data transformations are data normalization, advanced data parsing, etc.
Data Modeling
A data model is a diagram or flowchart that illustrates the relationships between data
- 9.1Data model creation(33) Ratings
Ability to create and maintain data models using a graphical tool to define relationships between data
- 9.1Metadata management(40) Ratings
Automated discovery of metadata with ability to synchronize and share metadata with other tools like Master Data Management
- 6Business rules and workflow(109) Ratings
Ability to define and manage business rules and workflows
- 4.5Collaboration(109) Ratings
Collaboration is enabled by a shared repository of project information and metadata
- 4.7Testing and debugging(110) Ratings
Tool to debug and tune for optimal performance
Data Governance
Data governance is the practise of implementing policies defining effective use of an organization's data assets
- 8.2Integration with data quality tools(22) Ratings
Integration with tools for cleansing, parsing and normalizing data according to business rules
- 8.2Integration with MDM tools(20) Ratings
Integration with master data management tools to ensure data consistency across the organization
Product Details
- About
- Integrations
- 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
Comparisons
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Reviews and Ratings
(205)Attribute Ratings
Reviews
(1-25 of 47)The GUI is intuitive, and the web interface helps to be up and running very quickly.
We have some issue related to the resources needed for some jobs, there's no visibility of the system resources used or auto-balancing of some activity to avoid the server to crash.
We don't like the billing mechanism being a cost based on the server CPUS because we host the server so we are already paying for it.
We would prefer a billing mechanism decoupled from the server resources for many reasons including the fact that it crashes on some jobs due to memory issue and upgrading the server would double the bill instantly for the same jobs. It doesn't scale naturally.
Few years ago when we started using it, it was a great player in the cloud ELT world, today it is suffering that while the interface is web, the engine itself is still monolithic and static, hard to migrate and move to a new machine.
We will be looking for other tools that have the creation of the data workflows and the actual scheduling/execution decoupled so that you can use a central hub to plan and create the logic and then decide in which region/sesrver to run them without having to worry about a full server being installed in every region.
Docker/kubernetes comes to mind, but implemented and managed effortlessly behind the scenes. We don't want to deal with it, just use the tool.
- Web interface is good enough
- Set of built in components available for orchestration/transformation
- Integration with target database (Snowflake for us)
- 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.
Can retrieve data from multiple different sources and handle them internally.
Expensive and being hosted by the client there's also the infrastructure burden of maintaining/paying for the server.
Considering the resources needed hence the license cost that scales with them (despite the fact that you host and pay for them already) I wouldn't suggest the tool to a small company and, once you are big enough you probably want to jump on bigger more mature tools.
Matillion is a nice niche player with some nice to have feature that are probably suited for a mid-size company with some money available to pay for the license but still a small infrastructure that just require one/two Matillion servers installed.
A global company with multi regions needs will drown under the burden of handling/updating/maintaining all the servers independently and pay for the cost of each one of them.
in my opinion, Meh
Maintaining source control in github is important to us.
We have used Matillion in the past for:
Replication - Copy from postgres, load to s3, perform transformation in redshift
Running python scripts
S3 data transfers - bucket to bucket
- graphical user interface
- Moving around widgets
- options for out of box operations
- connections
- source control maintenance (sync w/ github)
- poor logging, in my experience, can't see clearly what error is if something fails
- in my experience, difficult to connect with outside tooling
Experience the ETL with Matillion
- The jobs logging UI is very unique and helps in easy debugging
- It has a proper hierarchical structure. One can easily organise projects and related pipelines
- Access control and sharing necessary access is easy and quick
- I have seen good performance even with complex pipelines
- More features should be available with Git integration such as passing environment variables, schedules from git
- Need improvement in parallelism of job runs
- Sometimes cancelling a job gets stuck which can be improved
Matillion - Decent
- Scheduling ETL jobs
- Third party API connection components
- Not enough third party API integrations
- No version control easily usable
- Executing Snowflake scripts
- Oracle Database Connection and Data Retrieval
- Low Code programming by setting properties of the different components
- Parameter Passing between jobs
- New components for supporting other programming languages like R
- Upgrade Send Email component with more features
- Upgrade GIT Integration features
Good easy to learn ELT tool
- Extracts Nested JSON
- Had good DB support for multiple products.
- Runs in Azure where your Cloud is (may be).
- Upgrade process is sometimes quirky with no updates listed when there are clearly newer versions.
- Support is sometimes long winded and multiple people have to get involved.
- Docs could be expanded as not enough installed base to make forums or Google results useful in many cases.
Easy to get started and self learn, which is important.
- We leveraged Matillion’s no-code principals to make data manipulation easy for our internal customers. People who don't know how to use SQL no longer need to. Everything in Matillion is self-explained with no or little coding.
- We connected Matillion to our data warehouse to allow people to read raw data, transform it, then write results back to their sandbox databases. The drag and drop component design allowed customers to create complex data models at the speed of thought without any risk to production data.
- With sharing capabilities between projects enabled, everyone was able to help each other when questions arose which instilled a strong sense of collaboration and community.
- The new DPC version of Matillion uses Git principals like Commit, Push, Merge etc. This is perfectly fine for engineers, but for our use-case it means our customers will need to understand a basic level of Git. It would be great if they had an auto-commit-push setting which does it all for them.
Matillion has completely changed the way we serve data to our internal customers at the company; we've exported capability and empowerment rather than allowing ourselves to get swamped with tickets and requests for every possible data question. It's a great tool for getting people to self-serve their own answers to questions about their data.
Matillion Review
- ELT - Extract Load and Transform
- Mostly a direct copy of data into the destination is handled very well
- Managing secrets and all connections being handled using parameters/variables
- Some connections are not straightforward to set up
- Upgrades can get a bit complicated and require a backup instance to be created
- Ability to email data files
Replication with Matillion Saves Time
- Provides seamless, end-to-end replication
- Works tirelessly with the customer if there are any issues
- The customer service team needs to improve interaction with the customer
- Provide documentation to current customers on new features that are added so that we don't have to find out either ourselves or have to search through the FAQ pages
Great ETL for the wider organisation.
- Easy to learn.
- Easy to show complex calcs to stakeholders.
- Data lineage.
- Billing model.
- Git integration.
- Metadata management.
Matillion Helps Build Out Your Datalake
- File Imports
- Large Scale Data Manipulation
- Database Synchronization
- File Manipulation After Processing
- Built-in Error Reporting
- Versioning
- Really good user interface
- No complexity for anyone without much technical experience to get familiar with the tool
- Efficient in loading and transforming data
- Prevention of application crashes during huge volume of data load
- Improvement of button and default home page of UI
- Font size too small for few tabs
Great tool. Does a lot of the hard work for you. And lets the engineers focus on the data.
- ETL
- Data manipulation
- Integrates with data warehouses
- Containerisation. Hopefully this will arrive soon.
- Billing model. New hub model is much better but the previous market place model wasn't very flexible.
- External AD solution would be a big win.
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.
- 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.
- 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
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.
Matillion has been less good at extracting data from APIs. The functionality was found to be complex and it was unclear how to manage things like pagination and rate limiting in API calls.
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.
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)
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.
Matillion ETL - excellent cloud based data tool
- User friendly.
- Build complex workflows visually.
- Support is good.
- Easier email integration to mail out results.
- Version control of jobs.
- Ability to use external APIs to push data not just pull.
Less suited - Pushing output other than CSV or writing to tables.
Matillion - the swiss knife of ETL
- Python integration.
- Easy to set up, back up and restore.
- Scalable, works for any and all file types.
- Python libraries.
- Bigquery metadata.
Simple and powerful data aggregation tool
- Quick to set up
- Tailor-made for data warehouses (Bigquery, Snowflake, Redshift)
- Graphical UI to connect all the modules
- Easy to learn
- Customer response time needs improving
- SAAS model instead of charging hourly
- Lack of documentation
- Versioning logs not updated
My experience as a newbie to Matillion
- Connection to numerous data sources
- Validation of objects and components
- Ease of use to schedule run-times
- Variable driven code development
- Documentation examples
- Speed of processing
- Requires upfront investment in design of system processing.
- Assistance with upgrades