It is an incredibly user-friendly and intuitive tool, making the learning curve quite smooth. Its simplicity is such that one only needs a basic understanding of ETL processes to become proficient. With a plethora of connectors available, it seamlessly integrates with various data sources. Moreover, its native integration with AWS enhances its efficiency, utilizing lightweight instances and pushing processing tasks to registered instances, resulting in swift performance.

We have a lot of user-created excel spreadsheets. Matillion works very dynamically when it comes to fetching out data changes. It uses the metadata in the Excel document to map everything to your Snowflake which no other ETL can do. It cuts down the redundancy of remapping everything whenever somebody makes a change, especially while dealing with client-created files.

It's been able to do everything we require. It could fetch Excel files, SLS files, etc. It's pretty dynamic. I would say I am happy with their features.

The most valuable feature is the ability to put together pipelines that push down all of the logic into Snowflake. So none of the actual execution or none of the data you need to travel through. But we can do it in a GUI-based system, which is a lot easier to hand over to end-users. Most end-users, in my opinion, have an easier understanding of GUI-based tools than code-based tools. And Matillion just has a whole load of features that assist with that, they get integration allowing you to have the exact same as slow but apply it to different environments or push code changes through two different environments is really useful. And their ability to leverage different forms of iterators over variables control tables, etcetera, so that you can orchestrate a whole variety of things in one go instead of having to kind of train them up.

The most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation.

The product has a good user interface. I don’t have to write too many codes. I can design or create general data transfer and technical jobs through simple texts. If I want to repeat a job, I can do it without creating multiple pipelines. I can create multiple jobs with a single pipeline. It is a fantastic feature of the product.

• It works well with AWS Redshift: I have used Informatica, SnapLogic, and Talend and they do not work well with Redshift.
• Mid-pipeline data sampling: Without changes to pipelines, one can quickly and easily track down errors.
• Automatic database-object verification: A fundamental part of how Matillion works is ensuring objects, tables, columns, views, and other metadata are ready and available for use if, and when, a pipeline is started.
• Run-time parameters: These enable pipelines to be organized and modularized with minimum effort.
• An array of source-data components: Pulling data from wide tables, such as SFDC, can be setup in seconds. Using Sqoop to pull data to S3, for example, can take hours or even weeks to get right. It is worth noting that Matillion does not cost more if you need more source-data components (SFDC, Marketo, Google AdWords, RDS, MongoDB, etc.).
• A wide array of in-database DDLs and UDFs accessible from ETL are able to process unstructured data easily, without having to resort to EMR/Hadoop solutions.
• Integration with other AWS services: It can use Amazon SQS or SNS very easily to extend capabilities, such as doing micro-batch imports (near real-time updates) from source-systems.
• Python components using Boto and other libraries running on Matillion’s EC2: Matillion can push data from a data warehouse, via REST APIs, to target systems like DynamoDB and Marketo.

The most valuable feature of Matillion ETL is the ETL. The solution is open-source which provides advantages, such as good performance and high efficiency. Additionally, it supports three data types which eliminates predefining the data, and we can write script models in Python.

The new version with the Productivity Cloud is very simple. It's easy to use, navigate, and understand.

It also offers automated scalability in terms of handling large data volumes. It scales up automatically in the background, so you don't have to worry about infrastructure to do that.

The most valuable feature of Matillion ETL is its user-friendly graphical interface.

The positive aspect of this solution is that it provides a graphical interface for jobs. Another advantage of Matillion is its extensibility; if something is missing, it can be easily adjusted or custom components can be written. What I really appreciate about Matillion is that it allows us to schedule jobs, so we can track and monitor their execution on a daily basis. I also like how the solution is organized in Matillion; everything is clear and visible, and we can easily access any details we are interested in. Additionally, there is a useful feature for reporting errors, so we don't have to worry about error handling within the jobs themselves. This feature is very convenient as it saves a lot of time and effort.

Matillion ETL has great Git integration that is perfect and convenient to use.

• It is pretty easy to learn.
• No scripting is required.
• Being cloud native.

It is cost-effective. Based on our use case, it's efficient and cheap. It saves a lot of money and our upfront costs are less.

The most valuable features are the components for SFDC, RDS, Marketo, Facebook, and Google AdWords; built-in verification; and scheduling, restarting & logging.

On a Redshift project, before Matillion was released, two people literally spent over one month using Sqoop to pull very wide data tables from Safesforce.com to Redshift. On a new project using Matillion, it took me 10 minutes to set up and begin importing data from Safesforce.com.

Built-in verification and sampling is a fabulous feature for ETL engineers. Anywhere along the transformation-pipeline, one can check, see and sample the data. This saves days & weeks of effort and leads to a far more agile project.

The interface is very intuitive.

The most valuable feature of Matillion ETL is its ease of use. If you have had some experience with other solutions, such as Snowflake, the use of this solution will be simple.

It's very intuitive and it's super fast once the data's in the cloud. It's simple and visual, as well. I was self-taught. It's so intuitive and easy to use you can actually just teach yourself how to use it. They also have very good support with their YouTube tutorials. Those show you how to do various things if you need help figuring out aspects of the solution.

The tool's middle-dimensional structure significantly simplifies obtaining the right data at the appropriate level. This feature makes deploying our applications easier since we utilize a single source without publishing data from various sources. Consequently, presenting data becomes more straightforward, and customer interactions involve no copying or pasting, streamlining the exchange process.

With Matillion ETL, we read data from different warehouse source systems. We create a unified version of the data in the data warehouse using the ETL functionality. Mapping tables address the challenges of different source systems, ensuring the data is at the correct level of detail. It is very strong and comes with much functionality, including monitoring. 

Ease of use and a great way to present the ETL process to non-technical observers.

• It is pretty user-friendly, even for people who aren't super technical.
• It has good integrations with Amazon Redshift and other AWS services.

The loading of data is the most valuable feature of Matillion ETL.

The simplicity of this tool is nice. It has a good graphical user interface.

You can also do a lot of generic stuff in the tool. If there is good connectivity to a cloud database, such as Snowflake, and you can have a lot of Snowflake functionality in the tool.

Its ease of use.

• Analytics
• Integration with SAP and AWS.