We performed a comparison between Matillion ETL and Snowflake based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), MuleSoft, Matillion and others in Cloud Data Integration."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."
"The most valuable feature of Matillion ETL is its ease of use. If you have had some experience with other solutions, such as Snowflake, the use of this solution will be simple."
"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)."
"It has helped us to get onto the cloud quickly."
"The simplicity of this tool is nice. It has a good graphical user interface. You can also do a lot of generic stuff in the tool. If there is good connectivity to a cloud database, such as Snowflake, and you can have a lot of Snowflake functionality in the tool."
"The most valuable feature of Matillion ETL is its user-friendly graphical interface."
"It is pretty user-friendly, even for people who aren't super technical."
"Matillion ETL has great Git integration that is perfect and convenient to use."
"This is the advanced version of the cloud version, so it's really a flexible tool. If you have it implemented at home, you can access it from anywhere."
"The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
"The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do."
"The solution's customer service is good."
"Snowflake is a database, and it is very good and useful. The most interesting part is that memory management is very good in Snowflake. For a business intelligence project, SQL Server is taking a lot of time for reporting services. There are a lot of calculations, and the reporting time is shown as two minutes, whereas Snowflake is taking just two seconds for the same reporting services."
"I have found the solution's most valuable features to be storage, flexibility, ease of use, and security."
"Great scalability and near zero maintenance."
"Data Science capabilities are the most valuable feature."
"Going forward, I would like them to add custom jobs, since we still have to run these outside of Matillion."
"I found some of the more complex aspects of ETL challenging, but I grasped the concepts fairly quickly."
"Matillion’s on-premises capabilities don’t allow you to build something customized."
"The cost of the solution is high and could be reduced."
"It needs integration with more data sources."
"In the next release, we would like to have connections to more databases."
"The current version is a bit more limited because it's on a virtual machine, and everything executes on that one virtual machine."
"When using the SQL loader type there were not a lot of pre-processing features for the data. For example, if there is a table with twenty columns, but we only want to load ten columns. In that case, we can use a security script to select the specific columns needed. However, if we want to perform extensive pre-processing of the data, I faced some challenges with Matillion ETL. I did not encounter many challenges, but my overall experience is limited as I only have three years of experience."
"These aren't as crucial, but there are common errors sometimes where the database is down, or a table is nullified and a new table is added and you are not given access to that. With those errors, you don't have permissions."
"We would like to see more security including more masking and more encryption at the database level."
"Room for improvement would be writebacks. It doesn't support extensively writing back to the database, and it doesn't support web applications effectively. Ultimately, it's a database call, so if we are building web applications using Snowflake, it isn't that effective because there is some turnaround time from the database."
"An additional feature I'd like to see is called materialized views, which can speed up some run times. I'd like it to be able to be used where you can have multiple tables inside them; materialized view. That would be nice. As well as being able to run cursors, to be able to do some bulk updates and some more advanced querying, table building on the fly."
"In future releases, it can also support full unstructured data."
"Availability is a problem."
"Snowflake has to improve their spatial parts since it doesn't have much in terms of geo-spatial queries."
"I see room for improvement when it comes to credit performance. The other thing I'd like to be improved is the warehouse facility."
Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews while Snowflake is ranked 1st in Data Warehouse with 95 reviews. Matillion ETL is rated 8.6, while Snowflake is rated 8.4. The top reviewer of Matillion ETL writes "Efficient data integration and transformation with seamless cloud-native integration". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Matillion ETL is most compared with Azure Data Factory, AWS Glue, SSIS, Informatica PowerCenter and Informatica Cloud Data Integration, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Amazon Redshift.
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