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 When I wanted specific libraries of Python, I couldn't get it working on my instance because pip was out of date and it couldn't be updated.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.

Early on in the company, our non technical stakeholders could learn how to set up transformations on Matillion and build them up themselves. It is good to see the transformations visually.

If you can write SQL and schedule them using DBT, you should do that. Trying to set up the same transformation that you write in SQL in 15 minutes will take you 60 mins with Matillion because you have to think differently when using a click-click software like this.

Our experience with Matillion has been great. We've used to greatly improve and automate our data intake and transformation process.

I appreciate the ease of use of the tool. It is very simple and intuitive to build data pipelines using Matillion.

It's necessary to perform out own server maintenance to support the tool, which isn't too difficult, but can be a pain at times. If this were a hosted solution that would be easier.

We've been able to concentrate all data sources in one place and do a proper transformation and normalization of data to feed the Visualization layer.

Easy to use for non-tech (engineers) users.

Lacks testing stage before production and more flexibility to sample data.

Overall extract and load data strategies is very powerfull

Is easy and is real pay as you use, that is very important for latinoamerica business

That you can't write in other destinations

Matillion is very easy to use. It's simplicity allows you to drag an drop components to easily create orchestrations. It also simple to create shared jobs and use the components.

Although there is a decent set of components, they are not very versatile, hence I end up using a SQL script instead. For example, the S3 unload component does not allow one to specify some criteria and some fields are mandatory whereas I would not have to specify such specific criteria when doing this from an SQL script.

Easy to learn and use. The knowledge from other products is transferable. The documentation is amazing (one probably cannot understand how good without the experience). Support is always available and of good quality.

There is no restart-from-point-of-failure option for failed loads. Everything has to start from scratch or remaining jobs need to be run manually.

It was great working as well learning experience , hope Matillion will come up as industry leader.

Matillion integration with AWS services is flawless and has real time impact in batch jobs pulling data from on-premises to cloud platform.

Restricting the number of user can access Matillion, Lot's of time huge data set get stuck and fail with many other issues lastly better full log specifically for Developer to debug the issues.

The experience is very positive at the beginning but as the project grows and there are more and more workloads and data being processed Matillion starts to become a bottleneck.

It is very easy to implement features and changes to existing workload. It is very good for creating POCs

It is not scalable and has numerous limitations. Concurrency setting for Matillion limits the possibility of using it for multiple warehouses. It is highly insufficient when executing commands parallel and does not utilise the resources to it's full potential. The environment limitation is also very problematic when trying to scale.

I have been using Matillion since September 2018 and at the beginning i didn't like it very much as i dont had hands on experience using Matillion. But later my work has increased a lot using Matillion. So far i have had integrated bunch of sources using Matillion to data warehouse. I am liking it at this moment and no complains.

Matillion ETL is web based ETL tool and very easy to use from anywhere. It has most of the connectors for all data sources which makes my job to complete end to end development.

One thing I did not like about Matillion is, there is no need of Transformation job. Everything should be done at one place(Should be in Orchestration job). Also, the list of components are different in Orchestration and transformation jobs.

Matillion offers a powerful feature set within a robust UI. There are other options but none have the ease of onboarding that Matillion offers. The API adds a powerful layer to do advanced integrations.

Some threads have become unresponsive while running. This has been rare and was easy enough to resolve by resetting the service.

Its helping us build a data warehouse for visualizing debt and customer segmentation in our business. It means we are getting real insight into our business. Thank you!

User interface and range of connections. Powerful capabilities. Compatibility with AWS

Licensing is not flexible, Why cant you specify the number of concurrent users for a given instance? It comes with a fixed amount, if you don't like it, update to a much large and expensive instance that we do not need.

If you really use your data and work on a daily basis with your data warehouse you should consider using Matillion. We had no downtimes and the service is brilliant. We connected all of our data sources and it works really well. But it got its price. Compared to other solutions the pricing is good for growing businesses.

Connectivity Really good customer service Individual solutions if necessary No downtimes Hosted on Amazon

Pretty expensive A bit hard to set up initially

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

Overall it is user-friendly, easy to develop & deploy, secure ELT for big data use cases. It supports a lot of already built useful connectors, which helps to reduce marketability cost and time.

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

We use Matillion ELT to manage Data Warehouse. Support team provides consistent work around for issues.

Connectivity to Saas sources. Reliability and Customer Support team

RSD creation for Saas sources that do not have built in connector.

Easy to understand and follow processes. Easy to pass variable values between jobs. Works well with Redshift and S3.

Use of API's can be a little confusing to setup/configure.

Great tool

Easy to use, graphical way to do data flows on Google Cloud

The most missing functionality, is to be able to setup data destinations additionally to BigQuery

Target based ETL application. Cloud Native.

I would prefer it to support multiple target DBs like SQL Server, Oracle, MySQL, Redshift, Snowflake.

ELT, daily basis extract of data and ad-hoc tasks

Workflow Layout and clarity of all components

Environment Management, licensing model