We performed a comparison between Amazon Redshift 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 valuable features are performance, data compression, and scalability."
"The product is relatively easy to use because there is no indexing and no partitions."
"Amazon Redshift is a really powerful database system for reporting and data warehousing."
"The main benefit is that our portal for end users is running in AWS, so we can easily connect it to other AWS services."
"You can copy JSON to the column and have it analyzed using simple functions."
"The most valuable features of Amazon Redshift are that its fast and efficient. We have lots of TBs of data and it's very fast."
"It is quite simple to use and there are no issues with creating the tables."
"I find the most valuable features to be the MPP style of processing, which mostly all of the data warehouses provide. The ability to integrate all other AWS services, such as NSS and S3, with little effort is very helpful. The service is well maintained, there are update patches frequently."
"It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL."
"Snowflake is faster than on-premise systems and allows for variable compute power based on need."
"We find the data sharing and data marketplace aspects of Snowflake absolutely amazing."
"The most valuable features are the clustering, LS50, being able to change the size, the pay per use feature, the flexibility with many different sources and analytic applications."
"I like Snowflake's data exchange capabilities. It can exchange data with downstream systems and other vendor partners as well."
"Time travel is one feature that really helps us out."
"Very easy to use and easy to query."
"Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
"Sometimes, it's difficult to get the metadata from Redshift."
"They should provide a better way to work with interim data in a structured way than to store it in parquet files locally."
"The product must become a bit more serverless."
"The product must provide new indexes that support special data structures or data types like TEXT."
"The solution is unable to work fast."
"The OLAP slide and dice features need to be improved."
"Pricing is one of the things that it could improve. It should be more competitive."
"It would be nice if we could turn off an instance. However, it would retain the instance in history, thus allowing us to restart without beginning from scratch."
"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."
"I think that Snowflake could improve its user interface. The current one is not interactive."
"The cost efficiency and monitoring of this solution could be improved. It's easy to spend a lot on Snowflake and it does offer monitoring tools but they're pretty basic."
"Availability is a problem."
"The pricing of the solution should be much easier to calculate or find by yourself."
"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."
"I don't know about GCP, if they have connected for GCP. If they don't, they should allow for it."
"They don't have any SLAs in place. It would be better if they did."
Amazon Redshift is ranked 4th in Cloud Data Warehouse with 61 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 94 reviews. Amazon Redshift is rated 7.8, while Snowflake is rated 8.4. The top reviewer of Amazon Redshift writes "Provides one place where we can store data, and allows us to easily connect to other services with AWS". 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 Redshift is most compared with Teradata, AWS Lake Formation, Vertica, Microsoft Azure Synapse Analytics and Oracle Exadata, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Apache Hadoop. See our Amazon Redshift vs. Snowflake report.
See our list of best Cloud Data Warehouse vendors and best 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.
Although I verified it only in a specific case, I performed performance verification with Redshift, BigQuery, Snowflake.
Redshift has data redistribution occurred when searching under various conditions and performance was not good, but Snowflake holds data in small units called micro partitions, and also manages data for each column Therefore, operation like data redistribution was minimal and high performance was obtained.
Snowflake can also start multiple clusters in the same database, but has an architecture in which conflicts do not occur even when accessing the same data between clusters.
I recommend you to try it.
I am glad that you are already using it.