Matillion Reviews

-Extremely easy deployment with cloud formation template.
-Excellent pre-authored integrations that are easily extensible/customizable.
-Easy to use UI to build complex transformations.
-Extremely flexible logic with static and grid variables to intelligently execute jobs and branch as needed.

-No automated scheduling based on dependent table updates. (This is possible to set up, but not out of the box.)
-Support SLAs have gotten worse over time.

- 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.

- 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.

I've been using Matillion for about 2 and a half years. I've seen the software improve so much in that time. If I ever found a feature to be lacking, it would be included within the next couple release cycles. The software really seems to adapt as user needs have been evolving. Some of my favorite recent features are the ability to configure some components with just text (really saves me time) and the many Grid orchestration components which allow me to greatly reduce the complexity of the orchestration jobs.

UX is sometimes lacking or inconsistent. For example, let's say my goal is to replace an existing job with a new job of the same name. I delete the old job, and import the new one with the same name. All Orchestration components that used that job will understand to use the new job, but for some reason the scheduler doesn't.
Also, jobs will have validation errors simply because the components haven't been validated (grey borders). It can be confusing because you may be searching for an error in your work when all you actually have to do is revalidate the job.

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.

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.

Web-based, Runs in AWS so it can sit close to your data if you're using a cloud warehouse. You only have to pay per minute that you have the instance on which is a BIG plus.

Not nearly as many features and user-friendly data transformation tools as a competing software such as Alteryx has. As such, this tool is not as convenient or flexible for detailed data transformations. We mostly use it for bulk loading which it is very fast and good at.

Matillion is incredibly easy to deploy in AWS. In addition, the security and compliance aspects are all handled on the customer side due to the deployment method.

The UI is easy to use and the price point was the most competitive.

We haven't used it enough to encounter negative aspects yet but having to pay for the full amount of time the VM is up is going to be cost prohibitive for our small team.

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.

The collection of components; especially the integration components that hook into a very popular CRM and another quite popular ERP.

The python component. Depending on the box where your instance is hosted, this component will drag along like a broken train or move at the speed of shooting star.

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.

The platform is very user-friendly since it is based on drag and drop functions it makes the whole process easy and can be done by anyone. It is the best option since it is based on pay as you go so we can pay as much as we use. This has saved me a lot of money.

There are no negatives I have noted till now all the services are top-notch and up to the industry mark. This has helped a lot of engineers and businesses transform and automate their data.

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.

- 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.

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.

It is easy to use and quick to get started, there are many inbuilt APIs and transformations that integrate it across a broad suite of systems, and enable you to transform data for the business without having to spend too much time thinking about scripts or bespoke batch files.

The filter transformer is pretty minimal considering the power of the SQL it is utilising, it cannot use compound logic or reference other columns/objects in the query.
There is also optimisation issues in very complex workspaces.
Both of these have easy to use workarounds but it is unfortunate it is not supported more at surface level.

- Easy to orchestrate an ETL pipeline
- Integration with Redshift and other AWS services provides convenience
- Support team is easy to reach and have relatively quick response times
- They also support the other 2 popular cloud data warehouses, Snowflake and BigQuery
- Some components are available out to the box for easy integration
- Task history is useful for debugging and monitoring current state of ETL pipelines
- A GUI is provided for implementing complicated workflows, that can be easily followed

- Since it's mainly GUI based, it becomes difficult for data engineers to compare changes between old and new versions of an ETL.
- There are hard limitations for the number of concurrent users. This is part of the pricing model which is the reason.
- Integration with GIT is not yet available but we heard that it would be coming in the near future.

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.

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

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.

ease of use! someone with little code knowledge can come in and understand what's going on, it's very easy to follow along and see the transformation step by step

API connectors could be better. Could be more available, and a little more ease of use (especially with the endpoint mapping)

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.

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.

Makes for very fast development with lots of built in connectors. Visual layout of complex data pipelines is a big plus.

Out of memory errors. We use this for a lot of production applications. After 1 year of trying to fix OOM errors and doubling our instance size, we still get them monthly. I love matillion but I wish it were more reliable.

The billing structure contributes to the problem as well. We can't run matillion on a big instance without significantly increasing our licensing fees. I wish they were independant.

* If you've done any type of ETL work before, this will be a breeze. If you haven't it might take a few hours as opposed to minutes to get up and running
* The trial is full featured, get started today without waiting
* The software is on a EC2 instance in your own VPC in AWS. If you have company policies for how/where data can be processed -- you have complete control
* You can pay by the hour or the year, no hassle no fuss!

If you do encounter an issue the support organization is amazing. All questions were answered the same day, many within the hour.

More examples to work through on the transformation components would be helpful, but again... it's pretty easy

+ 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

Matillion is very intuitive.
The GUI is easy to use and fairly easy to learn.
The support team is great and they respond to your questions quickly.
I like how the Matillion team is frequently looking to add new functionality and features. The new keyword search functionality is very helpful.

Matillion works great extracting data from a variety of databases and is very efficient unloading onto S3 or Amazon Redshift. However, when we attempted to use it to unload large datasets to Microsoft SQL Server it was very slow and we experienced performance issues.