Matillion

Kommentare: We came to Matillion while looking for a tool that would allow us to orchestrate our load processes for Amazon Redshift. We'd used other ETL tools previously, were blown away by how easy it was to pick up and understand Matillion. We liked the simplicity, and the fact that we could always dig into the SQL that was generated. New features are added frequently, and we usually find one or two improvements that directly impact us with each release. Their support team are also very responsive, and Matillion are always keen to help you get the most out of their software, so there's a lot of support if you want it. 2+ years later, and we're using Matillion to run all our ELT jobs across various data warehouse projects, and very happy with it.

Vorteile: - Very intuitive design environment - super quick to learn.
- Components map closely to SQL capabilities in Redshift.
- Easy to view the SQL generated.
- Sample, row count, and data lineage make it easy to unit test as you build.
- Powerful management options via REST API (orchestration, Github integration, etc.).
- Native AWS integration.
- Aggressive release cycle, constantly adding new features.
- Easy to document in-workflow.
- Lots of third party integrations.

Nachteile: - User concurrency/licencing model (simple, but can't be customised to fit your need).
- Exception handling could be improved.
- A single Task View would be helpful for multi-environment/project support.

Vorteile: 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.

Nachteile: 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.

Kommentare: It was easy to get set up, and it worked great for pushing data into Snowflake as a data warehouse. However, we quickly realized that we would need yet another tool to get the data back out to the source systems to synchronize/integrate it. We could sort of do it with Matillion, but it required a lot of custom programming and was not very intuitive. We ended up using a different iPaaS tool that could handle traffic/integration in both directions.

Vorteile: It is extremely fast and easy to pull data from various sources and pipe it into Snowflake. The graphic interface lets this happen without programming.

Nachteile: There is almost no ability to get data back from your warehouse into the other systems to synchronize the data. It's great to have it all in the warehouse, but it seems pretty critical to have that data flowing back to other systems that are part of your environment. The pricing model is frustrating. You are billed for when the machine instance is ON, not when it is actively doing something. So, if you have a couple hours of job that run in a day, you have to shut down the machine to save money the rest of the day. With it shut down, development can't happen. So, we had to turn it on and off all the time. It would be much better if they billed as it is used, not as it is on.

Kommentare: 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.

Vorteile: - 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.

Nachteile: - 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.

Kommentare: I like working on matillion , but this tool can be made more flexible by providing some of the additional features.

Vorteile: 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.

Nachteile: 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.