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 stability of Amazon Redshift is good."
"Changing from local servers to the cloud is very easy. It's so nice not to have to worry about physical servers."
"The solution has very competitive pricing."
"This service can merge and integrate well with all databases."
"I have primarily used the Redshift Spectrum feature and found it most valuable."
"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."
"I found the Amazon Redshift computing services easy. I found the computing instances the most incredible in the solution."
"It allows you write complex queries and perform row by row processes."
"Snowflake is a database, and it is very good and useful. The most interesting part is that memory management is very good in Snowflake. For a business intelligence project, SQL Server is taking a lot of time for reporting services. There are a lot of calculations, and the reporting time is shown as two minutes, whereas Snowflake is taking just two seconds for the same reporting services."
"All the people who are working with Snowflake are extremely happy with it because it is designed from a data-warehousing point of view, not the other way around. You have a database and then you tweak it and then it becomes a data warehouse."
"The solution speeds up the process of onboarding."
"It is a very easy-to-use solution. It is user-friendly, and its setup time is very less."
"The initial setup is very simple."
"Snowflake is an enormously useful platform. The Snowpipe feature is valuable because it allows us to load terabytes and petabytes of data into the data mart at a very low cost."
"The Time Travel feature is helpful for accessing historical data and the ability to clone external tables is useful."
"The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management. It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure."
"The refreshment rate of data reaching Redshift from other sources should be faster."
"In our experiments, the handling of unstructured data was not very smooth."
"Migrating data from other data sources can be challenging when you are working with multibyte character sets."
"It lacks a few features which can be very useful, such as stored procedures"
"The initial deployment was complex."
"Amazon Redshift is a little more expensive than other products."
"The solution is unable to work fast."
"The OLAP slide and dice features need to be improved."
"The solution could improve the user interface and add functionality to the system."
"If we can have a feature where the results can be moved to different tabs, so that I can compare the results with earlier queries before applying the changes, it would be great."
"I have heard people having difficulty with the machine learning model, so there may be room for improvement."
"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."
"They need to improve its ETL functionality so that Snowflake becomes an ETL product. Snowpipe can do some pipelines and data ingestion, but as compare to Talend, these functionalities are limited. The ETL feature is not good enough. Therefore, Snowflake can only be used as a database. You can't use it as an ETL tool, which is a limitation. We have spoken to the vendor, and they said they are working on it, but I'm not sure when they will bring it to production."
"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."
"From the documentation, the black box is not very descriptive. Snowflake does not reveal how exactly the data is processed or sourced."
"The design of the product is easily misunderstood."
Amazon Redshift is ranked 4th in Cloud Data Warehouse with 59 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 92 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.
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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.