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"

Our business requires us to ingest large amounts of data from customers on a frequent basis. Once typical ELT has been performed, we create customized data stores which are used in a variety of ways including modeling, machine learning and a SaaS front end. Matillion has been instrumental in our ability to move this processing from file systems to Big Query where our performance has moved from days to hours.

- Provides great framework for visualizing complex queries with business users that are not SQL savvy - Logical flow of Transformation builder allowed quick transformation from file based to database based ELT - Just works! We have had very few issues with the tool over the 2 years I have been using it.

- Would like a more robust scheduler - Would like built-in messaging (e.g. for job failures/success) to be able to email out. This is not provided in the version for Big Query that we are running on GCS. - Better source code control (at the transformation/orchestration level, rather than the whole project) - Always could use additional documentation in how to use some of the more complex parts of Matillion.

I really like Matillion ETL but I was a bit disappointed with some of its limitations and quirks, like when Twitter updated his API all my jobs stopped working and the only thing I could do was develop everything again without using the Matillion component. When I was trying to make upsert procedures on RDS Databases, I was thrilled that the Matillion component has that option, bit it simply didn't work. It seems like these functionalities haven't got the same attention of the others, I contacted the Matillion support which is simply great and these things are still going to be fixed. When I wanted specific libraries of Python, I couldn't get it working on my instance because pip was out of date and it couldn't be updated. I tried to update and I messed up with my instance. Overall, Matillion is great, when you're creating a flow of data migration and you need to parse the data before and do some automations, but there are some cases when you need something a little more specific, that's when it becomes a pain.

The ease to use, Matillion has a great set of tools that make complex and difficult process more simple and fast to develop.

There are many tools in Matillion that doesn't have enough attention and because of that these tools are fragile, while some of them do not work.

I use it on a daily basis when we process incoming client data of different types. It can be used to build extremely complex workflows to handle data. The automation done on the platform rarely broke and was really stable even during peak data transfer intervals.

The changes made to the workflows on the platform are saved automatically which can be tricky if you make a change by mistake. So whenever you click a wrong button or value, it will be saved unless you undo the changes made and when working with huge complex workflows it can be really time-consuming to find the source of the issue.

We use Matillion to produce highly curated datasets for customers. Matillion has allowed us to move this workload entirely into the data warehouse where the final work product lives, and cut processing time from days to hours.

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.