Matillion Reviews

1.)All the components and transfomrations availability
2.)Specially oriented for data ingestion process using all aws services like rds, s3, sns, redshift
3.)easy admin, ssl setup
4.)very easy diagromatical representation of jobs

the latest button change for "switch version"

Matillion allowed us to move a legacy ETL pipeline to BigQuery with speed, precision, and confidence. It is now used exclusively by our team for all of our ELT needs. The user interface is clean, intuitive, and allows members of the team to be immediately productive. Onboarding new users has never been easier.

Feature parity between the different flavors (Redshift, Snowflake, BigQuery) is lacking, however, Matillion continues to make progress in narrowing the gap.

I like the bunch of API integrated in Matillion it helps me to directly grab the data from different sources without manually extra and import in my database.

I am using Matillion for Redshift from last more than 2 years. When i setup a project in Matillion with connection to a Redshift cluster, sometimes there is a need to extract the data from other instance of Redshift while running job in Matillion. In that case there is straight forward way of getting the data from other instance of Redshift like you have comments to extract the data from databases like SQL Server, Oracle etc. instead of first i need to run another job by connection second Redshift cluster and extract the records after that run different job to load the extracted records from S3 to main Redshift cluster.

1) Most of the components are user friendly.
2) Development of ETL orchestrations and transformation consumes less time.
3) Advanced features are available in some of the components makes the complex scenarios achievable.

1) OAuth document does not provide the details of proper permissions and access levels on account_id or client_id which are required for a connector.
2) Differentiation of naming convention of metrics between the console and matillion data model , mapping document of these naming conventions is not available.
3) Connector for Outbrain is not available.
4) Indirect file loading concept is not available , for example if we have five files with same structure , reg ex can not be used to load all files in a single component(s3 load,s3 put or excel)
and need to use the file iterator.
5) Loss of properties when the component configuration is changed from Basic to Advanced features , ideally the component should include all the properties of basic and then additional setting should be provided.

Well integrated with AWS. Great browser-based interface. Develop in the same place where the code will run, as opposed to other solutions I use that develop in Windows and run in Linux. Easy to schedule.

I have mixed feelings on the overall value. The hourly rate really adds up over time. This is probably my biggest misgiving. Otherwise, I sometimes get frustrated with the ELT model because it means if the feature you need isn't supported within Redshift, it's up to you to create Python scripts or Bash scripts to enable it.

My background is development and I love the simplicity of the Matillion, you can very easy transform your thought process into blocks in Matillion, and debug any issues at a very granular level.

Matillion crashes from time to time, meaning you need to log back on to the system, but its benefits definitely outweigh this small issue.

The ease of use is definitely the strongest aspect of Matillion. The GUI is exceptionally intuitive and even though the application flow speaks for itself, the documentation is also great for additional support.

You can hit a hard limit quite fast with the hardware when working with concurrent jobs running (Java Heap issues etc). You cannot increase the size of the instance (m4.xlarge) which means it becomes increasingly difficult to optimize. We are always trying to find work-arounds with the amount of data we need to load.

I love the GUI that Matillion employs - it makes creating and adjusting tasks very simple and transparent.

The scheduling of tasks is a little tricky, as we have to separately have to schedule the virtual machine to fire up and down. Once this is done though, it works faultlessly.

This tool helps in automating etl process.

Integration with python is limited. Need this feature

Ease of use and breadth of functionality.

We had a billing issue at one point when trying to renew but that was mostly due to AWS Marketplace and not Matillion as a product.

1) Easy to use
2) Several ingestion integrations
3) Custom RDBMS ingestion support
4) Robust transformation and Orchestration components

No availability of change data capture feature for many databases

Ease of use
Configured for AWS
Redshift compatible
Quick support turnaround

Not all connectors available - but new releases drop regularly

stable, close to SQL, integrated in AWS, fast

No data vizualisation (impossible to outpout the data directly in excel... )
Complicated to separate between orchestration in transformation

I like the stability of the product. We haven't updated our version since we started.

Can't use simple SQL Functions like CURRENT_DATE in FIlter Component. And no Automatic Update.

With Matillion, you can harness the power of major cloud data warehouses in no time.
What I love most is that you can give it to data engineers as well as ETL engineers with no prior experience with big data.

Error management and replay can be tricky to develop.

I could build a complete ETL process with absolutely no training at all in just a few hours. All of the components I expected to see where there, and heaps more. When I needed help - there it was!

Versioning and branching is difficult when developing, there is a total reliance on a unique component name.

Easy to use. Easy to move a lot of different processes into one place.

Problematic API support. ESC closing windows without any warning and I lose everything I prepared in that window! More support for operations not exactly about read like elasticsearch index creation or ability to do PUT, POST and DELETE with API.

easy to get into. Orchestrations and Transformations makes it easy to build flows. Push down to Snowflake

No standalone client, no easy way to automate/generate (somegow possible with grid variables though)

Easy to use. Quicker ETL. Comprehensive documentation

Nothing comes to mind. Perhaps round the clock support would be helpful, especially for customers located in Australia.

Snowflake integration works very well. In database features were what I was looking for.

Had to build most of my API calls using their Python script tool.

Ability to quickly build a fast, scalable pipeline for data ingestion

Honestly, there was very little. Whenever I had questions, customer service was extremely quick and helpful

It is a pay for what you use type of software. Most other ETL platforms are a flat monthly fee, sometimes at crazy prices. The pay for what you use model makes it easy to justify cost to leadership. You can schedule jobs to make sure you maximize your time.

The user experience feels a little dated. Some things could be better displayed/ explained.

+ Fast & easy to use
+ Completely embedded into AWS environement
+ Comes light, it's not overloaded with stuff no one uses
+ Some really innovative features

- Sometimes feels like not "fully under control", e.g. when a component runs into an OutOfMemory, the whole environement crashes. And there are different ways to trigger that...
- Scheduling overview could be more sophisticated, it's kind of hard to have a proper overview there
- Variable handling seems sometimes to be a bit difficult, e.g. when setting it in one process, it's not always set in sub-jobs
- In some cases, one can see that Matillion is still "under development": Same features are available in some components, but are missing in others

Logic drag & drop of ETL steps makes the design and documentation of each ETL processes much simpler.

Getting it setup and connected to our data warehouse seemed to be unnecessarily complicated. Luckily tech support is great and helped my DevOps team throughout the process.

From an engineers point of view one of the selling points for Matillion (apart from the absolute simplicity of use - at least to start with) is that it produces its own documentation !!

Sometimes the error messages can be confusing , but this is often down to the messages coming from BigQuery.

Its also not always obvious that it is producing SQL statement 'under the hood' and that can mean breaking sql statement size limits without realising it