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…
Matillion no-code features, from dream to tragedy
Small team supported by Matillion
Matillion Experiences.
Good integration and orchestration tool, not great for data transformation.
A good tool for your ETL needs, keep an eye on the bill and explore valid alternatives.
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
How Matillion Differs From Its Competitors
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Time Saved
Cost Savings
Business Outcomes
Onboarding
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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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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
- Connect to traditional data sources (127)7.575%
- Simple transformations (129)6.565%
- Complex transformations (128)5.353%
- Testing and debugging (114)4.444%
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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What is SolarWinds Task Factory?
According to the vendor, SolarWinds Task Factory saves time managing tedious ELT/ETL tasks with high-performing SQL Server Integration Services (SSIS) components that can be used within the Visual Studio environment to connect to nearly any data source. Task Factory’s components and tasks have been…
Features
Data Source Connection
Ability to connect to multiple data sources
- 7.5Connect to traditional data sources(127) Ratings
Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications
- 6.9Connecto to Big Data and NoSQL(87) 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
- 6.5Simple transformations(129) Ratings
Simple data transformations are calculations, data type conversions, aggregations and search and replace operations
- 5.3Complex transformations(128) 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
- 6.1Business rules and workflow(113) Ratings
Ability to define and manage business rules and workflows
- 3.8Collaboration(113) Ratings
Collaboration is enabled by a shared repository of project information and metadata
- 4.4Testing and debugging(114) 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
(210)Attribute Ratings
Reviews
(1-25 of 130)Why we still use Matillion after 2 years
- Excellent GUI to build data flows
- Flows backed up to GitHub for versioning
- Once set up it's full automated and so far no failures
- Perhaps some modernisation of the interface
- More granular cost reporting
Matillion no-code features, from dream to tragedy
- In my experience, no code user interface is painful to use
- In my experience, tool works for very simple use cases but doesn't support implementing complex workflows
- In my experience, no testing capabilities
- In my opinion, has the downsides of a SaaS (cost, low flexibility) and the downsides of self hosted (has to be hosted on customer infrastructure, handle updates...)
- In my experience, unreactive customer service
- In my experience, doesn't scale to high volumes of data
- In my opinion, high maintenance costs of no code pipelines
It is not appropriate for more complex use cases and teams which have engineering skills.
Small team supported by Matillion
- Scheduled jobs
- Transforming Data
- Customer Support
- API ingestion
- Change management / historic change log
Matillion Experiences.
- easy to develop ETL or ELT.
- Possibility of creating templates with its strong parametric structure.
- ready-made components.
- Matillion support.
- APIs.
- poor git integration.
- Having some bugs (eg, the Table creation component doesn't support the CURRENT_DATE() function).
- Expensive
- Ingestion of data from popular systems (Salesforce, Trustpilot.
- Orchestration of jobs with complex decision flows (retries, parameterized jobs, conditional flows).
- Error notifications.
- Git integration is limited and cumbersome.
- GUI-based data transformation makes it very hard to apply good engineering practices to data pipelines.
- Web-based development (there is no offline version) introduces a single point of failure for developers' interaction with the platform.
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 for cloud data integration.
- Matillion has a rich transformation library. It provides multiple functionalities, such as join, group by, pivot, various sources, and sinks.
- It provides the security capability as well. All the credentials can be securely stored in Matillion.
- Reusable templates can be built which reduces the redundancy.
- Time to production is very minimal.
- There is a scope of making it more developer friendly in terms of reusability.
- Many configurations required to set up the Matillion pipeline can be reduced significantly.
- In built python executable is quite slow.
Matillion enables us to manage all ETL/ELT processes without any dedicated data engineering resources.
- Easy to use interface - even for users without data engineering background.
- Many native components that do not require any "programming".
- Powerful generic profile creation to easily extract data from any API.
- Minor topic: adjusting a generic API Query profile can be a bit tricky. It would be great if we had proper EDIT functionality/flow.
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
Matilion helped grow my business
- Combines multiple data sources easily
- Reports and alerts issues effectively
- Customer service of professional
- Has been super stable for us over the last 2+ years
- Billing is confusing
- UX is good but isn't the best on the market
- Detailed help sometimes hard to find
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.
All That You Need in Your Daily ETL Work
- ETL
- API Integrations
- Speed of processing
- Improved data quality monitoring
- Maybe the UI could do with a makeover, it feels a bit old (but still nice though :-) )
- Easier integration with Slack, etc.
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
Use Matillion - Become the no code superman
- Drag and Drop
- Data Transformation
- Various Pre Built Connectors
- Easy understanding
- Pricing
- BQ Connections
- Less BQ Functionality
Great ETL for the wider organisation.
- Easy to learn.
- Easy to show complex calcs to stakeholders.
- Data lineage.
- Billing model.
- Git integration.
- Metadata management.
Simplicity in implementing ETL/ELT
We also use Matillion to execute Python scripts. We are working currently to configure Matillion to connect to Github.
- Executing Python scripts
- Data Lineage
- Easy to search of objects included in our project
- Creating job templates
- Jobs metadata to be available in Snowflake
- Error messages some times are not so clear
- Job Optimization recommendation
Matillion has so much components that fits majority of our business needs.
A mising point in Matillion is the metadata to be available in Snowflake.
Matillion Helps Build Out Your Datalake
- File Imports
- Large Scale Data Manipulation
- Database Synchronization
- File Manipulation After Processing
- Built-in Error Reporting
- Versioning
A Necessary tool
currently
We have near 50 automated jobs that runs every 5am and finished at 5.30am.
Also we matillion for extract data from HubSpot, zoom, brighspace, PostgreSQL, MySQL, cloud storage.
- Integration
- Performance
- Job developing ( if you have complex jobs, design the flow can be expensive)
- Cost
- Flexibility
On the other hand. Matillion help us for integrate data sources like netsuite, HubSpot and others.
Consider Matillion as an option.
Matillion Transforms Data Quickly and is reliant
- Transformation of data
- Efficient SQL query generation passed down to DB engine
- Structured and unstructured data handling options
- Data exploration and data transformation option availability
- Monitoring and reporting on errors
- Expansive API profile options
- Data quality testing / monitoring options
- Extended grid iterator limits