AWS Glue vs. Matillion

One of AWS Glue's most notable features that aid in the creation and transformation of data is its data catalog. Support, scheduling, and the automation of the data schema recognition make it superior to its competitors aside from that. It also integrates perfectly with other AWS tools. The main restriction may be integrated with systems outside of the AWS environment. It functions flawlessly with the current AWS services but not with other goods. Another potential restriction that comes to mind is that glue operates on a spark, which means the engineer needs to be conversant in the language.

Incentivized

When my team receives a request to import data in from a new place, it's great to have a tool where you can set up those imports in minutes, yet have the capabilities to create customized and complex orchestration as time allows. Because it's easy to send SFTP exports, my internal customers are sometimes surprised that it's not as easy to perform other exports such as e-mailed files or API integrations. If Matillion had output components as varied and excellent as the import components, it would be the perfect solution for so many things we do.

Incentivized

• It is extremely fast, easy, and self-intuitive. Though it is a suite of services, it requires pretty less time to get control over it.
• As it is a managed service, one need not take care of a lot of underlying details. The identification of data schema, code generation, customization, and orchestration of the different job components allows the developers to focus on the core business problem without worrying about infrastructure issues.
• It is a pay-as-you-go service. So, there is no need to provide any capacity in advance. So, it makes scheduling much easier.

Incentivized

• Matillion has a rich transformation library. It provides multiple functionalities, such as join, group by, pivot, various sources, and sinks.
• It provides the security capability as well. All the credentials can be securely stored in Matillion.
• Reusable templates can be built which reduces the redundancy.
• Time to production is very minimal.

Incentivized

• In-Stream schema registries feature people can not use this more efficiently
• in Connections feature they can add more connectors as well
• The crucial problem with AWS Glue is that it only works with AWS.

Incentivized

• Static and monolithic, it will show its limits when running multiple concurrent jobs.
• Github and versioning implementation is messy and broken. Don't use it.
• There's not way to see/query the system resources, just wait for a server to crash due to out of memory. An admin panel would be appreciated + some env variables with updated info.
• API implementation is cumbersome and limited.
• There's no concept of hub and worker engine, everything happens of the same server (designing workflows and executing them). Having separate light ETL engines to run job could be better. (sort of docker/kubernetes/lambda functions).
• Handling of variables is limited especially for returned values from sub components.
• Some components could return more metadata at the end of their execution instead of the standard one.
• Billing is badly designed not taking into account that the server is hosted by the client. Expensive.
• We had several issue with migration where starting a new instance was required and then migrating the content. It was painful and time consuming also have to deal with support and engineering team on Matillion side.
• CDC doesn't work as expected or it is not a mature product yet.

Incentivized

With the current experience of Matillion, we are likely to renew with the current feature option but will also look for improvement in various areas including scalability and dependability. 1. Connectors: It offers various connectors option but isn't full proof which we will be looking forward as we grow. 2. Scalability: As usage increase, we want Matillion system to be more stable.

Incentivized

We give 7 rating because of usefulness in AWS world without worrying about infrastructure and services interaction, it’s pretty out of the box gives us the flexibility to interact with them and use them. we take the data source in s3 from external system and then transform it using other AWS services and putting it back for other external services to consume in S3 form.

Incentivized

We are able to bring on new resources and teach them how to use Matillion without having to invest a significant amount of time. We prefer looking for resources with any type of ETL skill-set and feel that they can learn Matillion without problem. In addition, the prebuilt objects cover more than 95% of our use cases and we do not have to build much from scratch.

Amazon responds in good time once the ticket has been generated but needs to generate tickets frequent because very few sample codes are available, and it's not cover all the scenarios.

Incentivized

Overall, I've found Matillion to be responsive and considerate. I feel like they value us as a customer even when I know they have customers who spend more on the product than we do. That speaks to a motive higher than money. They want to make a good product and a good experience for their customers. If I have any complaint, it's that support sometimes feels community-oriented. It isn't always immediately clear to me that my support requests are going to a support engineer and not to the community at large. Usually, though, after a bit of conversation, it's clear that Matillion is watching and responding. And responses are generally quick in coming.

Incentivized

We were able to control on access and built various enviroment for implementation

Incentivized

AWS Glue is a fully managed ETL service that automates many ETL tasks, making it easier to set AWS Glue simplifies ETL through a visual interface and automated code generation.

Fivetran offers a managed service and pre-configured schemas/models for data loading, which means much less administrative work for initial setup and ongoing maintenance. But it comes at a much higher price tag. So, knowing where your sweet spot is in the build vs. buy spectrum is essential to deciding which tool fits better. For the transformation part, dbt is purely (SQL-) code-based. So, it is mainly whether your developers prefer a GUI or code-based approach.

Incentivized

We're using Matillion on EC2 instances, and we have about 20 projects for our clients in the same instance. Sometimes, we're struggling to manage schedules for all projects because thread management is not visible, and we can't see the process at the instance level.

Incentivized

• It had a positive impact on the way we build our data lake.
• It is the single source of truth for data structure (schemas/tables/views).

Incentivized

• Matillion has been the backbone of my company's analytical functionalities for 10+ years, so it has a good ROI.
• The price is ok for what our company built with it, but it starts to be less competitive if the tool is not used at its fullest.

Incentivized