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)6.565%
- Testing and debugging (109)5.555%
Reviewer Pros & Cons
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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…
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- Free/Freemium Version
- Premium Consulting/Integration Services
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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 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).
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Reviews and Ratings
(204)Attribute Ratings
Reviews
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March 18, 2023
Matillion for driving Data Mesh
Matillion is being used as a low code ETL tool for central platform as well as we make it available as self service platform within Organization. We also see a good potential to use Matillion CDC functionality (Matillion Data Loader) for meeting near real time demands
- 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
We have data residing in multiple systems across various applications using disparate database applications.
We were looking for a robust tool that would be able to bring in the data from these into our Datawarehouse.
And that is where Matillion ETL tool came into picture.
So we are using Matillion to integrate the data, transform the data by applying Business logic and finally making it available for the Business users to make informed decisions w.r.t Sales, Campaigns and Promotions and also to understand and address the pain areas of our Customers.
We were looking for a robust tool that would be able to bring in the data from these into our Datawarehouse.
And that is where Matillion ETL tool came into picture.
So we are using Matillion to integrate the data, transform the data by applying Business logic and finally making it available for the Business users to make informed decisions w.r.t Sales, Campaigns and Promotions and also to understand and address the pain areas of our Customers.
- 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!
We rely on Matillion to perform all ELT in our datawarehouse. Matillion has met Sophos' needs to increase data availability and reliability in the warehouse, increasing data operation efficiency by 40%.
- 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.
We use Matillion on all data pipelines. We gather data from source systems, update our data lake, and transform our data in dimensional formats for business reporting purposes.
- 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
- Loading S3 data lake files to Redshift
- Calling APIs and massaging data in Python and loading to redshift
- Automatic migration of files in S3
- Migrating data from Oracle to Redshift
- 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
Matillion is a user friendly interface, which allows our different data engineers to easily set up data integrations and transformations. It also support wide range of data sources , including cloud based databased, file systems and APIs, making it an excellent choice for our organization. Matillion has received high marks for its ease of use reliability.
- 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
We use Matillion on top of Snowflake to perform extensive ELT data transformation.Its easy orchestration helps non-technical users to create SQL based data pipeline and schedule those as per their requirement.
Reduces involvement of Tech team due to ease of use.
Snowflake acts a source and Target for most of our data system. We populate all our finance and other organizational reports using Matillion. Matillion is being used used in DWH, BI, Marketing and other teams.
Reduces involvement of Tech team due to ease of use.
Snowflake acts a source and Target for most of our data system. We populate all our finance and other organizational reports using Matillion. Matillion is being used used in DWH, BI, Marketing and other teams.
- 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.
We are using Matillion as our main ETL tool in order to move data from our RDS databases to our DWH (Redshift); during the process, we extract the data, perform some transformations, aggregations, and so on before inserting it on Redshift, where this data is used afterward by Quicksight and others B.I tools.
- 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
We use Matillion for all our redshift data warehouse ETL needs.
- 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
I have used Matillion in various projects in my company for different pharma clients for Life Sciences data. We were building solutions for clients which can help the analytic users and other down streams to consume data as per their requirements. In other Healthcare Analytics Projects, we were extracting the data from different sources like Facebook and Google Analytics and building a repository using Matillion ETL. Matillion was user-friendly and easy to learn and easily integrated with AWS Redshift and Snowflake DBs.
- 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.
We are using Matillion to centralize our data to a new data warehouse. Our primary use case is pulling data from a relational database (MySQL). I've been able to implement three different flavors of data sourcing, the two primary types being a full table load and incremental data loading of changed data into Slowly Changing Dimension and Fact tables in the DW. The performance of Matillion combined with Snowflake is astoundingly fast. We are also able to hit APIs to Zendesk and Hubspot easily to round out our integration with other SaaS vendors in our stack.
- 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
Matillion is helping resolve use-cases related to transparent orchestration workflows. These workflows often involve custom Python, SQL, staging locations, and sending data to external systems such as Salesforce and cross-channel marketing platforms all in one workflow. When FiveTran & DBT don't meet our exact requirements and use-case, we use Matillion to help resolve these use-cases in an easily understandable workflow that technical users, new engineers, or non-technical users can understand/troubleshoot.
- 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
Matillion is being used to transform and integrate data in our organization. Most of the data that we highly rely in decision making and planning is well analyzed by this great product. Data is safe for use in our departments can easily be saved in the cloud for free for future use.
- 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
I have been using Matillion since March and it has been a nice experience. It's helping a lot during our ETL process from RDS to Redshift, both on AWS. I really appreciate the software features and their support team is always able to clarify doubts and lead us to the best solution for our business.
- 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!
We have been using Matillion for a specific project in the SupplyChain area. The ETL works well and it was really easy to implement. We didn't use many objects, but we still were able to implement everything we needed, such us datamarts and file exports. We also tested the connection with SAP and we were happy to see it worked correctly. Something I think could be useful is a tool to move jobs between different environments: export/import upload. Json is ok but doesn't allow us to manage to version, and moreover, if you are moving many files, you need to manually substitute the original job with the new one.
- 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 is being used by the BI Team to orchestrate the population of the Data Warehouse. The Warehouse, in turn, is used to produce a range of reports across all business functions in the organisation. We use Matillion to ingest data from an application database (hosted in AWS), Salesforce, Netsuite and Google Analytics
- 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
We use it to get data from various sources into our data space. We use it within our company and also share it externally with our clients. It is very much useful.
- 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
Used by developers and business analysts in the IT department to extract and transform data into our Snowflake data warehouse. We have different data sources after a company merger and needed combined reporting. We also needed to pull data from third-party data sources such as Xero, Google Analytics, and so on.
- Breaks jobs down
- Graphics Interface
- Has lots of AWS documentation but not as much Azure.
June 29, 2021
Easy to implement and scale
We are implementing ETL workflows for other organizations that we consult for. It is currently being used for smaller sized clients across the whole organization. We use Matillion to automate the ingestion and transformation of data pipelines. We utilize Snowflake as a data warehouse, so we use Matillion as the tool to load data into the Snowflake database.
- Automation and scheduling
- Security and authorization
- Ease of use
- API Calls using python
- More community support and forums
June 29, 2021
Matillion Review
iQuanti is a Digital Marketing organization, which drives strategic decisions based on a data-driven approach and for this we use Matillion as our ETL solution tool for our organization, which is consumed by our Data Management team. We have large numbers of the digital platform from which we report and analyze the performance. Matillion helps us to automate most of our reporting needs by providing connectors to digital platforms like Google Analytics, Google Adwords, Facebook, Bing, JIRA, Google BigQuery, and various Data source connectors like Postgres, SQL, MongoDB along with AWS support as SNS, S3 etc, which provides lots of flexibility in today's world.
- 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
We use Matillion for Redshift to ETL data from various sources into our data warehouse which is used across the organization with the desire to share it with external users in the market too. It allows us to seamlessly integrate within the AWS stack and even outside so we don't have to think twice about whether we will be able to ingest data from any new source.
- 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
We use Matillion to bring together data from multiple sources - our application, Salesforce, Qualtrics, etc. - into a central data warehouse for use throughout the business in reporting, both internally and externally. Matillion performs the ETL that transforms this raw data into a structure in Redshift useful for reporting.
- 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.
Being used by the financial services department for ETL processes. It does the job of cleaning and transforming our data for internal and external reports.
- 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
Matillion is used by the software department for data integration, for syncing up data from the OLTP database to the OLAP system, and populating data for our data warehouse.
- 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!
We still have an old-fashioned process in our monolith environment to extract-transform-load from a SQL server data store. Currently the monolith is the main product of the CM brand and is still being heavily maintained. The way we are moving forward is to "unlock" the data from its current storage in order to have better analytics using event streaming. For the time being, the only way we are able to extract large amounts of data from our relational SQL data store is using the ETL process through Matillion into our data warehouse solution in Redshift.
- 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.