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Snowflake Analytics pros and cons

4.2 out of 5
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Pros & Cons summary

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Prominent pros & cons

PROS

Snowflake Analytics offers inbuilt infrastructure for executing queries without managing data volume, ensuring zero maintenance for data warehousing on cloud systems.
Features like time travel, zero copy cloning, data sharing, and scalability are highly useful for business intelligence and analytics.
The performance and computational power are strong, with the ability to handle large datasets efficiently and provide concurrency.
Snowflake Analytics is cloud-based, allowing fast deployment and eliminating the need for physical servers while being highly scalable and user-friendly.
It supports advanced features for data analysis such as materialized views and streaming capabilities for real-time data handling.

CONS

End-to-end execution of jobs isn't possible with Snowflake Analytics, requiring customization.
Moving data from legacy systems to Snowflake Analytics is not straightforward, and compatibility issues with processors can arise.
The cost becomes significant if there are many computations.
Snowflake Analytics lacks an on-premises option, making deployment challenging and reliant on external support services.
Improving integration with machine learning tools and AI could enhance Snowflake Analytics' usability.
 

Snowflake Analytics Pros review quotes

KR
Mar 6, 2024
Scaling is very high – there's no problem for scaling purposes. The learning curve is very small. And there are a lot of advanced features like handling duplicates, security, data governance, data sharing, and data cloning.
Javed Chowdhary - PeerSpot reviewer
Feb 14, 2024
Snowflake Analytics is pretty easy to use with the connectors for integration with the tools and systems in my company.
AS
Feb 28, 2024
Scalability-wise, I rate the solution a ten out of ten.
Learn what your peers think about Snowflake Analytics. Get advice and tips from experienced pros sharing their opinions. Updated: October 2025.
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Manoj Kambli - PeerSpot reviewer
Jun 27, 2024
Snowflake Analytics' predictive analytics elements, which incorporate AI, are good and easy to integrate.
Avijit Bhattacharya - PeerSpot reviewer
Mar 7, 2024
The Snowflake features I find most beneficial for data analysis are primarily related to analytics, particularly their features like materialized views and queues, which are especially useful for dashboarding purposes.
Vimalathithan M - PeerSpot reviewer
Apr 5, 2024
One of the key advancements in Snowflake Analytics is data sharing.
MandarGarge - PeerSpot reviewer
Jun 29, 2022
Very good flexibility and it offers computation completely decoupled from the storage.
MR
Oct 6, 2023
Time Travel and Snowpipe are good features.
reviewer2729628 - PeerSpot reviewer
Aug 13, 2025
The latest interface of Snowsight UI has added good capabilities and the interface is excellent.
reviewer2540286 - PeerSpot reviewer
Sep 3, 2024
It's cloud-based technology, so users can spin it up a lot faster
 

Snowflake Analytics Cons review quotes

KR
Mar 6, 2024
Machine learning in Snowflake isn't as advanced as in other products. I haven't heard of any successful industry-wide use cases of machine learning implemented in Snowflake. It might take a couple of years to reach the same level as Databricks.
Javed Chowdhary - PeerSpot reviewer
Feb 14, 2024
Snowflake's Snowpark is an area of concern where improvements are required.
AS
Feb 28, 2024
The product's cost is an area of concern where improvements are required.
Learn what your peers think about Snowflake Analytics. Get advice and tips from experienced pros sharing their opinions. Updated: October 2025.
872,098 professionals have used our research since 2012.
Manoj Kambli - PeerSpot reviewer
Jun 27, 2024
The pricing visibility is complex. If you understand pricing, you can estimate costs, but if not, it can be challenging.
Avijit Bhattacharya - PeerSpot reviewer
Mar 7, 2024
The scheduling of jobs requires improvement, particularly in terms of the user interface which currently lacks certain features found in comparable platforms.
Vimalathithan M - PeerSpot reviewer
Apr 5, 2024
Implementing everything on-premise is challenging because it require proper support from advisors, DBAs, and others.
MandarGarge - PeerSpot reviewer
Jun 29, 2022
If you have a lot of computations, it becomes very costly.
MR
Oct 6, 2023
The technical support is not very good.
reviewer2729628 - PeerSpot reviewer
Aug 13, 2025
We were experiencing errors while running reports and making connections.
reviewer2540286 - PeerSpot reviewer
Sep 3, 2024
Snowflake Analytics should probably have more built-in tools for master data management.