Google Cloud Pub/Sub vs. Maia by Matillion

If you want to stream high volumes of data, be it for ETL streaming or event sourcing, Google Cloud Pub/Sub is your go-to tool. It's easy to learn, easy to observe its metrics and scales with ease without additional configuration so if you have more producers of consumers, all you need to do is to deploy on k8s your solutions so that you can perform autoscaling on your pods to adjust to the data volume. The DLQ is also very transparent and easy to configure. Your code will have no logic whatsoever regarding orchestrating pubsub, you just plug and play. However, if you are not in the Google Cloud Pub/Sub environment, you might have trouble or be most likely unable to use it since I think it's a product of Google Cloud.

Great: Need to query simpler APIs, or utilize well known services such as GSheets etc.? Matillion has got some of the best and easiest to use connectors out there. Not so great: Do you need have a competent CI/CD flow that you will be able to update / compare from Matillion as well as other sources at the same time? Good luck, you will need to be extra careful, as you might have to have a deeper dive into your servers Terminal each time you have a git conflict.

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• With a pub/sub architecture the consumer is decoupled in time from the publisher i.e. if the consumer goes down, it can replay any events that occurred during its downtime.
• It also allows consumer to throttle and batch incoming data providing much needed flexibility while working with multiple types of data sources
• A simple and easy to use UI on cloud console for setup and debugging
• It enables event-driven architectures and asynchronous parallel processing, while improving performance, reliability and scalability

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• The user interface of your data pipelines makes it easier for people who aren’t as techy as data engineers to observe what's going on.
• Customer support is quick, not always as efficient as you would want it to be, but still.
• Nice documentation available.

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• Would be nice if the queue could be extended beyond 7 days.
• We found it a bit tricky replay unacknowledged messages when needed.

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• Matillion is brilliant at importing data -- it would be amazing to have more ways to export data, from emailed exports to API pushes.
• Any Python that takes more than a few lines of code requires an external server to run it. It would be great to have more integration (perhaps in a connected virtual environment) to easily integrate customized code.
• Troubleshooting server logs requires quite a bit of technical expertise. More human readable detailed error handling would be greatly appreciated.

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It serves all of our purposes in the most transparent way I can imagine, after seeing other message queueing providers, I can only attest to its quality.

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.

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It is easy to create Google Cloud Pub/Sub topics from both Web Console and CLI commands.

Google Cloud Pub/Sub supports creation of one or more subscriptions.

By supporting a BigQuery Pub/Sub subscription to automatically write to a BigQuery table it simplifies development by avoiding implementation of a custom micro service for writes to BigQuery.

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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.

I have never faced a single problem in 4 years.

It's very fast, can be even better if you use protobuf.

They have decent documentation, but you need to pay for support. We weren't able to answer all our questions with the documentation and didn't have time to setup support before we needed it so I can't give it a higher rating but I think it tends to be a bit slow unless you're a GCP enterprise support customer.

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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.

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

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Having used Amazon Web Services SNS & SQS I can say that even if the latter may offer more features, Google Cloud Pub/Sub is easier to use. On the other hand, usage of SNS & SQS as well as documentation and troubleshooting is easier with the AWS solution. Since we are not using GCP only for Pub/Sub the choice depends on other variables.

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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.

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You can just plug in consumers at will and it will respond, there's no need for further configuration or introducing new concepts. You have a queue, if it's slow, you plug in more consumers to process more messages: simple as that.

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.

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• Increased Efficiency with reliable and Google managed services up all the time wit Disaster Recovery in place as well
• Definitely Lower costs being a cloud based solution and easier to setup
• Faster Project delivery and go to market plan for the business use cases basis this technology at the back end

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• 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.

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Invited by TrustRadius (TR) on Vendor's Behalf

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