We performed a comparison between Amazon EMR and Snowflake based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution helps us manage huge volumes of data."
"One of the valuable features about this solution is that it's managed services, so it's pretty stable, and scalable as much as you wish. It has all the necessary distributions. With some additional work, it's also possible to change to a Spark version with the latest version of EMR. It also has Hudi, so we are leveraging Apache Hudi on EMR for change data capture, so then it comes out-of-the-box in EMR."
"It allows users to access the data through a web interface."
"Amazon EMR's most valuable features are processing speed and data storage capacity."
"It has a variety of options and support systems."
"Amazon EMR is a good solution that can be used to manage big data."
"The solution is pretty simple to set up."
"The project management is very streamlined."
"The solution's computing time is less."
"The solution is stable."
"Its speed and performance were the most valuable. Easy configuration of Snowflake in any cloud was also a benefit."
"The most valuable feature is the clone copy."
"A user-friendly and reliable solution."
"It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL."
"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."
"Can be leveraged with respect to better performance, auto tuning and competition."
"The dashboard management could be better. Right now, it's lacking a bit."
"There is room for improvement in pricing."
"The legacy versions of the solution are not supported in the new versions."
"The product's features for storing data in static clusters could be better."
"We don't have much control. If we have multiple users, if they want to scale up, the cost will go and increase and we don't know how we can restrict that price part."
"There were times where they would release new versions and it seemed to end up breaking old versions, which is very strange."
"As people are shifting from legacy solutions to other technologies, Amazon EMR needs to add more features that give more flexibility in managing user data."
"The most complicated thing is configuring to the cluster and ensure it's running correctly."
"The pricing of the solution should be much easier to calculate or find by yourself."
"The design of the product is easily misunderstood."
"The solution could use a little bit more UI."
"There are some challenges with loading unstructured data and integrating some message queues or brokers. In one project, we had a problem connecting to one of the message queues and we had to take a different route altogether on Microsoft Azure."
"It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud."
"We are yet to figure out how to integrate tools, such as Liquibase, to release changes to our data warehouse model."
"There are always a few operation updates here and there that can be made."
"The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template."
Amazon EMR is ranked 9th in Cloud Data Warehouse with 20 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 92 reviews. Amazon EMR is rated 7.8, while Snowflake is rated 8.4. The top reviewer of Amazon EMR writes "Provides efficient data processing features and has good scalability ". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Amazon EMR is most compared with Cloudera Distribution for Hadoop, Azure Data Factory, Amazon Redshift, Apache Spark and Microsoft Azure Synapse Analytics, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Microsoft Azure Synapse Analytics. See our Amazon EMR vs. Snowflake report.
See our list of best Cloud Data Warehouse vendors.
We monitor all Cloud Data Warehouse 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.
