Matillion Data Productivity Cloud Reviews

We're populating a data warehouse, which is the primary focus, but we are also using it to populate our data lake with unstructured data.

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.

Ideally, I would like it to integrate with Secrets Manager as well as the AWS. 

I haven't had any issues with stability.

It's highly scalable. It takes upon itself the Redshift scalability, so it's very good.

We'll be accommodating more data sources going forward. Up until now, it's been a pilot, but we've basically got about another 22 data sources to bring on board. This has been a very successful proof of concept and we will definitely continue using the Matillion going forward.

Technical support has been very helpful. They've got quite an efficient help desk and they've always come back to me with good technical answers within 24 hours, which is very acceptable.

We had previously used a homegrown ETL system and used a combination of IBM Cognos and ClickView as the presentation layout. They both had their own ETL steps inside them. What we're doing now is we're taking all of the data and moving it into one central data lake warehouse, which is sitting in Redshift, and controlling all the ETL in one place, as well. We're looking to switch off the legacy products now.

Essentially, I want all my data sitting in AWS and I wanted one product that could handle everything, that also needed to be lightweight. I didn't want to go with one of these big Informatica's or other similar tools that are out there, which are all licensed based and very expensive. I wanted something lightweight that was easy to use and relatively cheap.

The initial setup is very straightforward. You can set your first job up in literally minutes. We had our first jobs up almost instantly.

For deployment, the latest version that's just come out integrates with Git, so you can do all of your conversions just using the native Redshift code commit, which is the Git repository. You can actually just do it and it's turnkey. It's very easy. You don't need any people, actually. For maintenance, ideally, we would need about a couple of people. 

We have a small team doing all of the data requirements.

We handled the implementation themselves. That's the beauty of the product. We didn't need to get any external help.

It probably is a bit early to measure ROI because at the moment we are having to run all of our processes in parallel and a lot of our existing infrastructure has hidden costs. It definitely will be a lot cheaper going forward and we'll be able to show that. Once we're able to switch off all our legacy servers we'll see very clearly that there's an ROI. 

With on-prem servers, there are always hidden costs, but moving to the cloud makes billing and any extra costs very transparent.

The solution is very cheap. You're paying $2.50 an hour and if you set your service up, which you can do, you're not getting charged. Currently, our ETL process is just an overnight process that runs for about an hour. I can start and stop my server just for an hour if I want to and spent $2.50 a day for an ETL solution. There are no additional costs. It plugs into the AWS marketplace. It's very easy to manage that cost. And if you don't want to use it for a while, you just switch off the EC2 instance and you're not getting billed.

We did have a look briefly at Informatica, but it was just too industrial and over the top in terms of price.

Also, Matillion was the only tool that was fully integrated into Redshift. The other tools were basically bolt-ons onto the cloud, but they weren't using the full extent of the card processing capabilities. For this tool, Matillion is actually using the full processing capabilities of Redshift, which includes what they call Massively Parallel Processing on all of their nodes. It's actually a cloud-native product. It was built specifically for Redshift and that was the main difference. There are other tools we could have used, but they required separate EC2 instances to be commissioned and they just didn't seem to integrate as well into the cloud space.

We're using the latest enterprise version of the solution with the public cloud deployment model.

They're constantly improving themselves. I'm quite pleased with the pace of the number of changes that are coming out all the time.

It's a great product and I think it's very competitive. I would recommend the solution.

I would rate the solution nine out of ten.

• ETL process
• Data warehouse

It has improved the costs of managing my customer’s data.

• Analytics
• Integration with SAP and AWS.

It needs integration with more data sources. I would also like a better UI because it is complicated to manage it.

It makes loading and transforming data on Snowflake very fast, easy, and affordable. It is also stable.

It can scale up/down Snowflake warehouses. My client’s size is a mid-sized environment.

It takes less than five minutes to set up and delivers results. It is much quicker than traditional ETL technologies. It loads data into Snowflake from dozens of sources, including S3 and RDS, multiple databases, and APIs.

Purchasing this solution through the AWS Marketplace was quick and easy. 

It was procured through the AWS Marketplace because it keeps things simple. They offer retail-like checkout and bill through your existing Amazon Web Services account.

The AWS pricing and licensing are a cost-effective solution for data integration needs.

It is perfect for when you need your data to never leave your environment using a robust tool. It also ensures the best security practices are deployed within your AWS account.

I have also integrated this solution with Microsoft Azure, but the best performance is with AWS.

• It enabled an enterprise data-warehouse to be set up and operated, quickly and cheaply.
• The pipeline UI provides a means to present solutions to analysts and non-tech management for review and agreement.

• 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.

Compared to the likes of traditional ETLs, like Informatica, SnapLogic, and Talend, or even raw Python scripts, this product needs no improvement, as it is so much better.

Any new product like this has teething problems that get solved pretty quickly in the next release. Better user documentation with more examples would be helpful, especially in areas with run-time parameters or JavaScript inserts.

There have been some issues with stability over the first year, but Matillion support is very responsive. I have allowed them to log into our system on occasion.

There are no issues with scalability if one strictly does all transformations in-database, using Redshift’s DDL/SQL.

All the ‘heavy-lifting’ is done by Redshift, as it is MPP. Simply adding more nodes deals with scalability. It is worth noting that Matillion does not cost more if you add more Redshift nodes.

If one uses Python components (as opposed to UDFs), one may encounter scalability issues.

The CPU utilization in WatchTower, of Matillion’s single EC2 (it is not, itself, MPP), will peak. Therefore, it is best to keep a close watch over what your data engineers are doing with Python components.

I would give technical support a rating of 5/5.

We used Informatica, SnapLogic, and Talend. They do not work well with Redshift and they cost more. They do not understand MPP and much of what they do is outside of Redshift, i.e., not in-database.

You need to put them on a bigger EC2 or buy multiple licenses and have multiple EC2s to manage, in order to get scalability.

The initial setup was very straightforward, as it’s all done from the AWS Marketplace. A wizard steps you through the process of setup. Due to Matillion’s clean and clear architecture, there is not much to configure before one is up and running.

Regardless of the quantity of your data, the size of your cluster, or variety of source systems, the price of Matillion is the same.

The only variable that changes what you pay Matillion is the size of your data engineering team.

• If your team is just one or two people, then you can just use the [t2.medium @ $1.37/hr]
• If you have a bigger team, you will need [m4.large @ $2.74/hr] or even [m4.xlarge @ $5.48/hr].

As soon as you can, lock in the yearly discounted price with Matillion, as your level of support availability will increase.

We evaluated Informatica, SnapLogic, Talend, Sqoop, and pure Python scripts. Don’t go with any of these if your data can be categorized as any two of the following: volume, variety, and velocity.

• Experiment and test it ASAP
• Watch all the videos from Matillion
• Join their webinar series
• Talk with existing users

Remember, what Matillion does is simply orchestrate the required jobs. It stands back and lets Redshift do what it is good at.

We use it to migrate data from in-house databases and other data sources into Amazon Redshift.

• It is able data sync reliably.
• It ensures that we are compliant with our legal requirements.

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

• It could have better integrations with other databases and other services.
• I would like to have more customization available.
• Going forward, I would like them to add custom jobs, since we still have to run these outside of Matillion.

It is very stable. We have not had to deal with many issues. 

It is running at almost 100% CPU for most of the night. So, it is fairly stressed.

It scales okay. It takes up a good amount of computing resources while it is running, but we wouldn't have too much trouble giving it a little more if it needed it. We have a lot of data, therefore it is hard for me to guess how much we send through it.

I haven't personally dealt with the support.

The integrations with a lot of the AWS tools, services, and databases are very convenient. 

It works with DynamoDB, Redshift, Salesforce, and Aurora databases. It has good integrations with all of these.

Purchasing it through the AWS Marketplace is pretty convenient. There is a little bit of back and forth in terms of the licensing based on the machine size, but it seems to have worked out well. it is convenient to have it all as part of our AWS billing.

It is not necessarily a cheap solution. However, it's reasonable priced, especially with the smaller machines that we run it on.

We also evaluated Xplenty. 

We chose Xplenty because we wanted to able to have the data live in our VPC, through our network, and not exit our network. Also, the cost was good.

It does the things that it does fairly well, but it would be nice to have some more features, like custom jobs.

Try different tools as much as you can. Make sure the different data that you are trying to sync fits in with the integration the tool provides (or at least most of them). Otherwise, you are going to be paying a lot for not using most of its features.

Our primary use case is ETL.

We allow non-technical people to use Matillion to load data into our data warehouse for reporting. Thus, it is easy enough to use that we don't always have to get a technical person involved in setting up a data movement (ETL).

Its ease of use.

In the next release, we would like to have connections to more databases.

It seems very stable. We have never had any problems.

We have about 4000 employees.

I have never dealt with the technical support.

The integration and configuration of this product on our AWS environment is very easy to do and flexible.

It integrates extremely well with Amazon Redshift.

It was very easy to purchase through the AWS Marketplace, but it was also expensive.

The prices needs to be lower.

We did not consider any other products.

Ask about pricing details.

Bringing data from different sources onto our Snowflake data warehouse.

• It has helped us avoid a lot of red tape due to compliance. 
• It has helped us to get onto the cloud quickly.

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

It is not an end-to-end platform for ETL. It brings in the data. To complete the pipeline, they might want to include some connectors which would put the data into different platforms. This would be helpful.

We are working with different platforms. Most of the connectors that we are looking for are included, but sometimes scripting is required. The good thing is we can reach out to support and have them create the custom connector for us. This can probably be improved.

We do not put much stress on it. We run it as a batch right now and spin it up on demand. So, we run it for three hours, then we shut it down. It is not real-time, and there is not a lot of streaming as of now, but it is running in the batch.

The size of our environment is not big. We started six months back. Right now, we only use one node, which is moving the data onto our data warehouse in Snowflake. This node is also very small at this time. 

Eventually, we will grow big and quickly, because we just had our three drugs approved. Therefore, a lot of data is going to come over. We will be moving this over to our data warehouse, which will need to increase significantly.

The technical support treats us well. They already have a support portal, and they are responsive, which helps.

We haven't used any of the on-premise solutions. What we used before was SQL Server Integration Service (SSIS), and when we were moving to the cloud, we wanted to use something that was cloud native (AWS).

The integration and configuration of this product in our AWS environment was excellent.

We are integrating it with SQL Server and the data coming in is from the on-premise file server. That's what we are connect with right now. Eventually, we will be pulling the data from Google Cloud and Twitter.

We are still in the process of moving the data over, so there are no data points as of now.

You probably don't even need to reach out to the company sometimes to purchase it. You can go to the AWS Marketplace. It's very easy to spin up, and the configuration is also easy. It spins up in your own AWS account. The only way you can get the product now is via the AWS Marketplace.

Their pricing is simple. They charge you by the hour. Whatever EC2 instance time that you have been running it for, that's what it's going to charge you for. The licensing is not based off of the per user or per server. They are going by the type of instance you spin up and how long you've been running it, so easy peasy.

The other products that we considered were SSIS and Informatica.

We chose Matillion because of the flexibility of the data and the company does not store data on its platform. As a life sciences company, which is HIPAA compliant, we didn't want to move the data over to the platform, so that's why we selected Matillion. It also has additional components that we did not have to pay for, as those features are included with the data. We can scale horizontally with it.

Give it a shot. See how easy it is to get started with the product, because the scripting which is required is minimal. Anybody who is familiar with the SQL Server platform and with SQL scripting can easily pick it up and run with it,

Overall, it is a really good product.

We use it for archiving and storing data.

"It has made our lives much easier," This is what my teammates who were using the other stuff before have said. Then, they moved it to Snowflake. Now, it is much easier and faster to use than before.

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.

• Performance can be improved for efficiency, and it can be made faster. 
• Latency could be reduced. Sometimes, it takes longer to fetch data out of it. There are network issues because we experience a little lag.
• While the UI is good, it could be improved in its efficiency and made easier to use.
• It can be used by different consumers. So, I would recommend to the company to promote more, because people don't know much about it. If they promote more, they can sell it. They need more marketing.

It is pretty stable, but you can't blindly rely on it. On a scale of one to ten, I rate it around an eight.

It can scale to a great extent. It can handle the load that we are putting on it, which is about 5TBs.

The technical support was good at troubleshooting. The issue that was sent to them was resolved in a couple of days, so it was resolved quickly. 

The integration and configuration was pretty easy. It was completed in about two months.

It saves a lot of time.

I have heard from my manager and other higher ups, "This product is cheaper than other things on the market," and they have done the research.

Anybody can help to configure and train on it, learning how to use it. This will help speed up the process.

We use the AWS version only.

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

It has enabled building a data warehouse within three months from the ground up to support WMS reporting.

It would be great to have the ability to move windows around to dock in different locations/external windows.

This would involve an ability to physically pin, or move the windows within Matillion (for Redshift).

I know that they can be resized to some extent – but it would be great to collapse the windows, or move them -- similar to moving a tab from a browser so that it's separate from the main GUI.

We have been using this solution for six months.

We have not encountered any stability issues.

We have not encountered any scalability issues.

Matillion's support is great. They are fast to respond, always helpful, and they have great documentation. This includes articles, training videos, and regular software update building on customer feature requests. I would give the support a rating of 10/10.

I am not aware of any previous solution.

The setup was straightforward. The user interface is very intuitive and purchasing from the marketplace was simple.

If you are unsure, just send Matillion a quick email, and they’ll get back in touch to help.

We did not evaluate any other options.

Just go ahead and take advantage of the initial free period for evaluation. The on-demand price is also very competitive.