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."Amazon Redshift is very fast. It has really good response times. It's very user-friendly."
"It is very easy to dump data into the tool."
"The most valuable feature of Amazon Redshift is its ability to handle really large sets of data."
"The tool's most valuable feature is its parallel processing capability. It can handle massive amounts of data, even when pushing hundreds of terabytes, and its scaling capabilities are good."
"The solution has very competitive pricing."
"In terms of valuable features, I like the columnar storage that Redshift provides. The storage is one of the key features that we're looking for. Also, the data updates and the latency between the data-refreshes."
"It's scalable because it's on the cloud."
"Setup is easy. It's a fast solution with machine learning features, good integration, and a good API."
"The features I found most valuable with this solution are sharing options and built-in time zone conversion."
"I like Snowflake's data exchange capabilities. It can exchange data with downstream systems and other vendor partners as well."
"The querying speed is fast."
"It is a very easy-to-use solution. It is user-friendly, and its setup time is very less."
"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."
"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."
"I have found the solution's most valuable features to be storage, flexibility, ease of use, and security."
"Great scalability and near zero maintenance."
"There is some missing functionality and sometimes it's so difficult to work in. We need to convert these functionalities using VACUUM inside Amazon Redshift and then it causes some complexity."
"The refreshment rate of data reaching Redshift from other sources should be faster."
"Planting is the primary key enforcement that should be improved."
"Pricing is one of the things that it could improve. It should be more competitive."
"The solution has four maintenance windows so, when it comes to stability, I think it would be better to decrease their number."
"Running parallel queries results in poor performance and this needs to be improved."
"They should provide a better way to work with interim data in a structured way than to store it in parquet files locally."
"It lacks a few features which can be very useful, such as stored procedures"
"I am still in the learning stage. It has good security, but it can always be more secure."
"There are a lot of features that they need to come up with. A lot of functions are missing in Snowflake, so we have to find a workaround for those. For example, OUTER APPLY is a basic function in SQL Server, but it is not there in Snowflake. So, you have to write complex code for it."
"The cost of the solution could be reduced."
"If you go with one cloud provider, you can't switch."
"There is a scope for improvement. They don't currently support integration with some of the Azure and AWS native services. It would be good if they can enhance their product to integrate with these services."
"Portability is a big hurdle right now for our clients. Porting all of your existing SQL ecosystem, such as stored procedures, to Snowflake is a major pain point. Currently, Snowflake stored procedures use JavaScript, but they should support SQL-based stored procedures. It would be a huge advantage if you can write your stored procedures using SQL. It seems that they are working on this feature, and they are yet to release it. I remember seeing some notes saying that they were going to do that in the future, but the sooner this feature comes out, it would be better for Snowflake because there are a lot of clients with whom I'm interacting, and their main hurdle is to take their existing Oracle or SQL Server stored procedures and move them into Snowflake. For this, you need to learn JavaScript and how it works, which is not easy and becomes a little tricky. If it supports SQL-based procedures, then you can just cut-paste the SQL code, run it, and easily fix small issues."
"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."
"We would like to see more security including more masking and more encryption at the database level."
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.