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 product offers good support for the data lake."
"It is quite simple to use and there are no issues with creating the tables."
"Setup is easy. It's a fast solution with machine learning features, good integration, and a good API."
"The solution's flexibility is its most valuable feature. It's also easy to scale and has relatively painless pricing."
"The valuable features are performance, data compression, and scalability."
"It allows for the storage of huge amounts 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."
"It's very easy to migrate from other databases to Redshift. There are migration tools dedicated for this purpose, enabling migration from other databases like MS SQL directly to Redshift. The majority of the scripts will be automatically transposed."
"The pricing is reasonable and matches the rest of the market."
"Working with Parquet files is support out of the box and it makes large dataset processing much easier."
"The speed of data loading and being able to quickly create the environment are most valuable."
"Data Science capabilities are the most valuable feature."
"Its speed and performance were the most valuable. Easy configuration of Snowflake in any cloud was also a benefit."
"It helped us to build MVP (minimum viable product) for our idea of building a data warehouse model for small businesses."
"Snowflake has a variety of other ETL provisions that they provide. You can use your own ETL pipeline. Additionally, they provide adapters, and they are always evolving, it is a well-developed solution."
"The Mbps they have established is quite a bit faster than any other data warehouse."
"Should be made available across zones, like other Multi-AZ solutions."
"It would be useful to have an option where all of the data can be queried at once and then have the result shown."
"There are physically too many pipelines for a company of this size to maintain. For a data scientist, it's very difficult to learn the data in all of these different environments."
"Planting is the primary key enforcement that should be improved."
"Query compilation time needs a lot of improvement for cases where you are generating queries dynamically."
"The customer support could be more responsive."
"For people who struggle with IAM or role-based management, the setup isn't easy."
"In our experiments, the handling of unstructured data was not very smooth."
"If they could bring in some tools for data integration, it would be really great."
"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."
"Snowflake has to build more capabilities because they have only built very few adapters, but they're growing and they're building. They should provide provisions to collect ETL pipeline capabilities, reduce developer work, and make more rapid application development, rather than some customizations. There are very few options, but they are building. I hope they will build ETL rapid application development provisions with more variety."
"Pricing is an issue for many customers."
"Its pricing or affordability is one of the big challenges. Pricing was the only thing that we didn't like about Snowflake. In terms of technical features, it is a complete solution."
"Snowflake could improve migration. It should be made easier. It would be beneficial if it could offer some OLTP features. One of our customers was using Oracle for both data warehousing and OLTP workloads, and they were able to migrate their data warehousing workloads to Snowflake without major issues. However, for some of their OLTP requirements, such as needing a response time of fewer than 10 milliseconds for certain queries, Snowflake is currently unable to provide that."
"They should improve the reporting tools."
"I have heard people having difficulty with the machine learning model, so there may be room for improvement."
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.