Likelihood to Recommend AWS Data Exchange fits best for scenarios where you have datasets that you would like to sell and you want to deliver it to anyone who would like to purchase it. It really beats having to set up downloads via your own website or portal. However, it can get complicated to manage if you're trying to deliver a dataset a client has already paid for.
Read full review It is very well suited for ETL on the cloud. Whenever there is something that can be accomplished with no code or little code, Matillion is a good tool. However, if your pipeline requires a lot of customizations, Matillion should be avoided.
Read full review Pros Simplified data delivery Ability to create any amount of data products Ability to integrate payment plans with data products Tracking data downloads and users Integration with other AWS data services Read full review We leveraged Matillion’s no-code principals to make data manipulation easy for our internal customers. People who don't know how to use SQL no longer need to. Everything in Matillion is self-explained with no or little coding. We connected Matillion to our data warehouse to allow people to read raw data, transform it, then write results back to their sandbox databases. The drag and drop component design allowed customers to create complex data models at the speed of thought without any risk to production data. With sharing capabilities between projects enabled, everyone was able to help each other when questions arose which instilled a strong sense of collaboration and community. Read full review Cons Integration with more data sources Ability to deliver data to clients without AWS accounts Inclusion of direct data downloads in addition to asynchronous methods Read full review I think a non-CLI approach to installing and uninstalling python libraries would be nice. I mean, it isn't difficult to install a python library via Linux or CLI, but I imagine most companies don't feel comfortable allowing Matillion users to go on a virtual server and installing it themselves. Requirement.txt file for installing libraries would be simple, and maybe that could also be used to uninstall libraries as well......or maybe the library gets automatically downloaded if it is imported into a python script but the library doesn't exist. Python Component is lacking very much in terms of UI. It would be unrealistic for me to suggest Matillion build its own EDI, but it would be nice if a python component could connect to a local IDE. Right now, if you want to write any decent length python code, you are going to be stuck copying and pasting your code from your local IDE. It is also very difficult to debug in Matillion because you can't set breakpoints. Local IDE integration can resolve that. I would like to have more templates to copy from for certain simplistic scenarios. For instance, a template for a job that fails which sends an AWS SNS with the Job name, component it failed on, and the error message. It wasn't as simple as I thought it would be to figure out and having to use a shared job for such circumstances can be painful because you have to export a bunch of variables. There should be a drop down list for Global Matillion variables as it is difficult to remember at times. Read full review Likelihood to Renew There have been a lot of problems with ADX. First, the entire system is incredibly clunky from beginning to end.First, by AWS's own admission they're missing a lot of "tablestakes functionality" like the ability to see who is coming to your pages, more flexibility to edit and update your listings, the ability to create a storefront or catalog that actually tries to sell your products. All-in-all you're flying completely blind with AWS. In our convos with other sellers we strongly believe very little organic traffic is flowing through the AWS exchange. For the headache, it's not worth the time or the effort. It's very difficult to market or sell your products.We've also had a number of simple UX bugs where they just don't accurately reflect the attributes of your product. For instance for an S3 bucket they had "+metered costs" displayed to one of our buyers in the price. This of course caused a lot of confusion. They also misrepresented the historical revisions that were available in our product sets because of another UX bug. It's difficult to know what other things in the UX are also broken and incongruent.We also did have a purchase, but the seller is completely at their whim at providing you fake emails, fake company names, fake use cases because AWS hasn't thought through simple workflows like "why even have subscription confirmation if I can fake literally everything about a subscription request." So as a result we're now in an endless, timewasting, unhelpful thread with AWS support trying to get payment. They're confused of what to do and we feel completely lost.Lastly, the AWS team has been abysmal in addressing our concerns. Conversations with them result in a laundry list of excuses of why simple functionalities are so hard (including just having accurate documentation). It was a very frustrating and unproductive call. Our objective of our call was to help us see that ADX is a well-resourced and well-visioned product. Ultimately they couldn't clearly articulate who they built the exchange for both on the seller side and the buyer side.Don't waste your time. This is at best a very foggy experiment. Look at other sellers, they have a lot of free pages to try to get attention, but then have smart tactics to divert transactions away from the ADX. Ultimately, smart move. Why give 8-10% of your cut to a product that is basically bare-bones infrastructure.
Read full review 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.
Read full review Usability It has been easy to train new employees who don't have previous experience with Matillion. It is quite self-explanatory. There are quite a few things that can be done with Python, however, we have not really looked into this feature much but likely will do in the future. Mostly, it is drag and drop of components and environments can be set up so easy to set up connections as well.
Read full review Support Rating 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.
Read full review Implementation Rating We were able to control on access and built various enviroment for implementation
Read full review Alternatives Considered Matillion ran circles around Stitch and
Striim both in functionality, setup, and performance. There was no real comparison.
Fivetran massively outperforms Matillion in pretty much every facet of the production from setup, maintenance, visibility, and usability. It already has the ability to connect any data source to a destination regardless of database type. Why we chose Matillion over
Fivetran is that, for our current needs, Matillion provides us with the functionality that we need and a much more competitive price for a smaller company.
Read full review Scalability I have been able to connect Matillion to AWS Aurora Databases, MySQL databases, Rest APIs, Files in AWS S3, etc. Being able to load all of that disparate data into one datalake has made data mining and reporting a lot simpler. I wish everything could be implemented as easily as Matillion.
Read full review Return on Investment Reduced time to publish datasets for sale by more than 80% Increased net profit from dataset sales by ~10% Reduced data delivery time to clients by 15% Read full review Saving us time reduces our need for headcount Allows us to collaborate on data-eng pipelines in a transparent way with non-technical stakeholders, ensuring accuracy and continuity Allows us a single platform to log and manage all of our pipelines to pin-point where something failed and why Always has a solution to very common data engineering tasks, i.e., real-time data, connectors, pre-built workflows, etc. Read full review ScreenShots