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 most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation."
"It's been able to do everything we require."
"It has good integrations with Amazon Redshift and other AWS services."
"Matillion ETL is one hundred percent stable."
"It is an incredibly user-friendly and intuitive tool, making the learning curve quite smooth"
"It takes less than five minutes to set up and delivers results. It is much quicker than traditional ETL technologies."
"The product has a good user interface."
"The most valuable feature of Matillion ETL is the ETL. The solution is open-source which provides advantages, such as good performance and high efficiency. Additionally, it supports three data types which eliminates predefining the data, and we can write script models in Python."
"I like the idea that you can assign roles and responsibilities, limiting access to data."
"The solution is stable."
"My company wanted to have all our data in one single place and this what we use Snowflake for. Snowflake also allows us to build connectors to different data sources."
"Snowflake is faster than on-premise systems and allows for variable compute power based on need."
"It is very fast and the performance is great."
"The product's most important feature is unloading data to S3."
"The most valuable features are sharing data, Time Travel, Zero Copy Cloning, performance, and speed."
"It is a cloud solution with many useful features. It has the data science capability. It can transform data and prepare data for a data science project with scalability."
"I am looking forward to seeing the expansion of the source range for their data loader product."
"I found some of the more complex aspects of ETL challenging, but I grasped the concepts fairly quickly."
"Going forward, I would like them to add custom jobs, since we still have to run these outside of Matillion."
"One of the features that's in development is data privacy in the cloud, along with further SAP integration. For connectivity to SAP systems."
"The improvement area could be possible if the tool provides better integration capabilities with other ecosystems, including governance tools or data cataloging tools, as it is currently an area where the solution is lacking."
"While the UI is good, it could be improved in its efficiency and made easier to use."
"To complete the pipeline, they might want to include some connectors which would put the data into different platforms. This would be helpful."
"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."
"It needs a bit more rigor and governance, which is something you don't get with newer tools. This makes it less enterprise scalable. Its governance and structure can be enhanced, which would really be valuable. I would like to see some kind of prebuilt functionality in terms of having almost like a pre-built data warehouse. A functionality for generating automated kind of pieces would be good."
"I see room for improvement when it comes to credit performance. The other thing I'd like to be improved is the warehouse facility."
"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."
"The complexity of the initial setup of Snowflake depends on the use case. However, Snowflake itself, we don't set it up. The difficulty comes from the ingestion patterns, depending on what data I'm putting in, what kind of enrichment, and what additional value we have to add. However, it does tend to get complex because we have a lot of semi-structured data which we need to handle in Snowflake. There have been some challenges."
"There is room for improvement in Snowflake's integration with Python. We do a lot of SQL programming in Snowflake, but we go to a different tool to program when we have to in Python."
"The scheduling system can definitely be better because we had to use external airflow for that. There should be orchestration for the scheduling system. Snowflake currently does not support machine learning, so it is just storage. They also need some alternatives for SQL Query. There should also be support for Spark in different languages such as Python."
"Snowflake has to improve their spatial parts since it doesn't have much in terms of geo-spatial queries."
"They do have a native connector to connect with integration tools for loading data, but it would be much better to have the functionality built-in."
Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews while Snowflake is ranked 1st in Data Warehouse with 92 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, Informatica PowerCenter, SSIS and Informatica Cloud Data Integration, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Amazon Redshift.
We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
