Matillion Data Productivity Cloud Reviews

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.

It is helping to make Makerbot a data-driven company.

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.

More frequent releases are needed, due to API changes from Google, Marketo, and Facebook. They frequently release upgrades to their API and consequently frequently deprecate the older version when only a few months old. The only way to use the Matillion components for these APIs successfully is for the Matillion release process to step up to the plate and have far more frequent "minor" API releases (as opposed to "major" product releases).

Even having these automated might not be a bad idea. Some customers willing to pay might open up a new revenue stream for "platinum" service, to take the headache out of this very valuable set of marketing components in Matillion.

I only encountered stability issues when accidentally performing EC2-intensive Python jobs (i.e., not Redshift-intensive SQL). These can kill the Matillion EC2 instance.

I have not encountered any scalability issues.

Customer Service:

Customer service is excellent.

Technical Support:

Technical support is above-and-beyond.

SnapLogic and Informatica: too slow; for MPP, they are just glorified and expensive Python schedulers.

Python scripts: high maintenance.

Initial setup was straightforward.

I implemented it myself.

We achieved ROI in <1 year.

The first two weeks are free; pay by the hour for smallest instance for next 2-3 months; after that, take out yearly discounted rate from AWS Marketplace for instance/devs in team.

We also evaluated SnapLogic, Informatica, Talend, and Hadoop.

The mindset of the traditional ETL tools is to off-load transformation to another server/DB. This totally misses the point of MPP and especially of Redshift. Load the data into Redshift early and then transform it inside Redshift ("ELT" not "ETL"). Matillion orchestrates the loading and transformation "pipelines", then gets out of the way whilst Redshift does what it is good at (i.e. the "grunt work").

In a project where we migrated from on-prem solutions to the cloud, we used Matillion and Snowflake, which streamlined the process significantly.

Matillion ETL's ability to conduct end-to-end data migration is valuable. We can create jobs, monitor them, and manage workflows effectively.

The product's scalability needs improvement. Perhaps adding more connectors would be beneficial.

The product is quite stable and can handle complex data integration tasks well.

I rate the platform scalability around six or seven. Depending on the specific architecture, parallel processing needs, and data types involved, it could be optimized.

I haven't contacted the technical support team, but the online documentation and community resources are quite sufficient.

A team of two to three ETL architects and data engineers is required to work on deployment. 

We can monitor and manage real-time data pipelines, analyze task logs, and automate data pipelines wherever possible. We also apply parameterization to improve efficiency using the product.

It adapts well to changing data volumes and types. I would recommend it, especially for cloud data integration.

I rate it a seven or eight. 

The tool's primary use case is implementing Snowflake, including building a data warehouse atop our source systems and facilitating data exchange with customers and suppliers utilizing Snowflake.

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. 

The tool's lineage is very weak. 

I have been using the product for three and a half years. 

The tool is stable. 

I haven't contacted the technical team yet. 

Matillion ETL's deployment can be done in-house. 

Matillion ETL is expensive. 

The tool seems to reduce complexity rather than boost performance. The overall process remains somewhat intricate. I don't think we've observed any performance improvements using my team. I rate the overall product a seven out of ten.