I have used Snowflake for an end-to-end data solutioning as a warehouse, including all its capabilities such as ingestion and any implementations that were needed.
Snowflake AI Data Cloud
SnowflakeExternal reviews
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Supports real-time pipelines and testing through dynamic features and flexible data replication
What is our primary use case?
What is most valuable?
Snowflake has evolved significantly over time. Initially, they started with scalability, but more recently, they have introduced streaming capabilities, real-time and dynamic tables, along with various connectors.
Snowflake is well integrated with other solutions. I have used the Snowflake Zero-Copy Cloning feature in the past while prototyping data in lower environments. This feature is helpful as it saves a lot of time during the data replication process.
I have utilized the Time Travel feature multiple times while conducting testing. I have typically used the Time Travel feature for testing to see what the state of data was at a specific point in time. This feature is helpful, and Snowflake also has good RBAC policies with masking capabilities and policies that can be implemented.
Snowflake's data sharing capabilities are good for enhancing collaboration within the team. Additionally, Snowflake has introduced Snowpark and AAML integration, which makes it feasible to perform CICD operations.
What needs improvement?
Snowflake is currently stable, but it can be improved further. They have a couple of information schemas that can track account usage. If more connectors were brought in and more visibility features were added, particularly around cost tracking in the FinOps area, it would be beneficial.
I think the pricing for Snowflake is fair, and customers need to cautiously monitor their usage, as that is the customer's responsibility.
For how long have I used the solution?
I have worked with Snowflake for more than five years.
What do I think about the stability of the solution?
Snowflake is currently stable.
What do I think about the scalability of the solution?
Recently, Snowflake has introduced streaming capabilities, real-time and dynamic tables, along with various connectors.
How are customer service and support?
I have not had a direct interaction with Snowflake's customer service or technical support. I have only interacted with them for billing calls, and those interactions have been fine without any challenges.
How would you rate customer service and support?
Positive
What other advice do I have?
I have not explored multi-cloud deployment in Snowflake extensively enough to understand how it impacts an organization's data strategy for cost, performance, or compliance. I can rate Snowflake an eight out of ten based on my limited encounters with their support team, as those interactions have been positive. My company are customers only, not partners of Snowflake. I would rate this product nine out of ten overall.
UsingSnowflake for Data Analysis
What do you like best about the product?
Snowflake helps our team easily gather and study a huge amount of data from different places. It works just as we expect when we build our business plans letting the team create, test, and understand and fast and smoothly.
What do you dislike about the product?
Snowflake needs a simple AWS setup to run properly in the cloud. Its main tool, snowflake studio, works fine but could be a faster and smoother.
What problems is the product solving and how is that benefiting you?
We connect data from different places, study it, and build Business plans using Snowflake. Thats why its an important part of how we analyze and create our business models.
Impressive Data Storage, but Lacks Integrated Infrastructure
What do you like best about the product?
The ability to store large datasets is staggering, and ability access at faster speed is something I like
What do you dislike about the product?
Snowflake being an independent service rather than an add-on to the infrastructure is a feature that's often highlighted.
What problems is the product solving and how is that benefiting you?
Snowflake solves the problem
Simple SQL Queries Across Data Sources—Straightforward and Effective
What do you like best about the product?
The ability to use simple SQL language to query different data sources that have been dumped into the datalake.
What do you dislike about the product?
Nothing that comes to mind, it's a pretty straight forward tool
What problems is the product solving and how is that benefiting you?
It's allowing us to quickly query and create tables for Data Analytic and Dashboarding consumption.
Have prioritized security while managing multi-agent data migration and cloud adoption
What is our primary use case?
In terms of solutions such as security, automation, or monitoring, security is prime. In agentic, I am building the agentic assets. From a data migration perspective, we are building the multi-agent accelerator which will help to migrate legacy data to a cloud platform or new platform, such as Databricks and Snowflake. Everywhere security is a prime concern nowadays. Nobody will allow you without the security assurance.
Regarding assessing Snowflake's data sharing capabilities in terms of enhancing collaboration, currently there isn't end-to-end or B2B sharing of data.
What is most valuable?
We utilize Time Travel with Snowflake because this is a very useful feature. Everyone finds it crucial because in conventional data platforms, it's very difficult to handle these kinds of things. This feature is essential, though I don't have the use cases currently; it is just there for implementation.
Regarding Snowflake's automated scaling and suspension features, this auto-scaling is very significant. We had a comparison with Databricks and Snowflake a few months back, and this auto-scaling takes an edge within Snowflake; that's what our observation reflects.
What needs improvement?
If I were to rate support, I would say it's about an 8 or 9. There is always room for improvement. What things you are going with to ask the support and how we manage the relationship matters a lot. Overall, we are very happy with Snowflake support.
For how long have I used the solution?
I have been familiar with Snowflake since the last three to four years because within Genpact we have started using it.
How are customer service and support?
I am satisfied with the work of technical support from Snowflake; they are responsive and helpful.
How would you rate customer service and support?
Positive
What other advice do I have?
This is a service industry, service company.
Regarding satisfaction with pricing for Snowflake, I'm not in detail about Snowflake. I'm managing all the agentic world for the last two years, GenAI agentic. I don't have much insight on that part. The actual licensing is managed by the COE leads working with the sourcing team.
I rate Snowflake 8 out of 10.
Powerful platform for handling large data workloads easily !
What do you like best about the product?
I like how effortless it is to scale up or down based on workload. Queries run fast and the separation of storage and compute keeps performance consistent even when multiple users are active. The interface is clean and the integration with BI tools like Power BI and Tableau works perfectly for analytics projects.
What do you dislike about the product?
Costs can climb quickly when queries run continuously. Some monitoring options feel limited unless you use external tools. The learning curve for role management is also a bit tricky at first.
What problems is the product solving and how is that benefiting you?
It solved our data silos problem by centralizing everything in one warehouse. Different teams now access the same clean data without duplication. It saves hours each week since we don’t have to export or transform files manually. Collaboration between analytics and engineering teams is smoother which helps deliver reports faster.
Good decision for cloud data warehousing
What do you like best about the product?
Depending on the size of your warehouse, we can handle a large amount of data without performance issues. This would be very difficult with an on-prem server.Further, the separation of storage and compute helps with resource management.Additionally, we're a Tableau shop, and Tableau has a built-in connector with Snowflake that is reliable and efficient.
What do you dislike about the product?
Cost management can be challenging. This is where the size of the warehouse comes into play (see What do you like best about Snowflake?). If you optimize the size of your warehouse small, costs will be smaller. Along these lines, it's best to understand credit usage early to make sure you're managing effectively. But overall, few negatives that can't be managed with some forethought.
What problems is the product solving and how is that benefiting you?
Our infrastructure is quite complex, but since Snowflake is fully managed, we no longer have to worry about provisioning or ongoing maintenance. This allows our data architecture team to focus on more valuable work, while our data analytics team benefits from uninterrupted access, as maintenance issues no longer cause downtime. Scalability is another key advantage—Snowflake efficiently processes large volumes of data without requiring our architecture team to oversee the infrastructure. This not only saves time but also enables quicker queries, even as our total data volume increases. Ultimately, this leads to faster project scaling, quicker insights, and allows us to devote less effort to managing our data strategy.
Efficient, scalable, and reliable data warehouse for modern analytics
What do you like best about the product?
Snowflake’s ability to handle large volumes of structured and semi-structured data seamlessly is its biggest strength. The separation of compute and storage lets us scale resources independently, which improves performance during heavy reporting workloads. It also integrates smoothly with BI tools like Power BI and Tableau, making it easy to deliver insights quickly without manual data preparation.
What do you dislike about the product?
Although Snowflake is highly efficient, query costs can add up quickly if the virtual warehouses aren’t managed properly. Also, real-time data streaming capabilities are still somewhat limited compared to other cloud-native services. A more intuitive cost-monitoring dashboard and tighter integration with streaming platforms like Kafka would make it even more powerful.
What problems is the product solving and how is that benefiting you?
Snowflake has helped centralize large data sets from multiple sources—HR, finance, and donor systems—into one scalable warehouse. This unified platform allows us to run complex SQL queries, automate reporting, and generate real-time dashboards in Power BI. It also simplified data governance and eliminated storage constraints we had with traditional on-prem databases. Overall, it enables faster data-driven decision-making and supports analytics initiatives without extensive infrastructure management.
User Point of view
What do you like best about the product?
The most important part is we can do different types of big data engineering and is very easy to use. We can do the etl process in a single go. The code can be implemented easily in the process and we can connect snowflake support for any help. I mainly use it everyday as most of my work is dependent on it. It supports pyspark as a new feature.
What do you dislike about the product?
The cortex is newly integrated so many updates are yet to come. So still waiting for that.
What problems is the product solving and how is that benefiting you?
We are solving different types of business problems like data integration, data transformation and data security. Even we are performing data masking and integration for the third party business.
The cloud data powerhouse that just scales with you
What do you like best about the product?
What I appreciate most about Snowflake is how many thoughtful, practical features exist beneath the surface that solve real operational problems:
The search optimization service has been transformative for high-cardinality lookups; queries searching by specific IDs or emails that used to take 30+ seconds now return in under a second, without any query rewrites or manual indexing.
I love the account-level result caching. It's not just that my queries benefit from caching; if anyone in the organization runs the same query, everyone benefits. This makes dashboards and recurring reports incredibly snappy without additional engineering effort.
The directory tables on external stages feature eliminates so much custom logic. It automatically tracks file metadata in cloud storage, making incremental data loading trivial without building elaborate file-tracking systems.
Finally, tag-based masking policies have scaled our data governance beautifully. Instead of applying policies table-by-table, we tag columns (PII, sensitive financial data, etc.), and policies auto-apply across hundreds of tables. It's governance that actually keeps up with our data growth.
It has these layers of operational intelligence that reduce busywork and let teams focus on actual analytics rather than infrastructure babysitting.
The search optimization service has been transformative for high-cardinality lookups; queries searching by specific IDs or emails that used to take 30+ seconds now return in under a second, without any query rewrites or manual indexing.
I love the account-level result caching. It's not just that my queries benefit from caching; if anyone in the organization runs the same query, everyone benefits. This makes dashboards and recurring reports incredibly snappy without additional engineering effort.
The directory tables on external stages feature eliminates so much custom logic. It automatically tracks file metadata in cloud storage, making incremental data loading trivial without building elaborate file-tracking systems.
Finally, tag-based masking policies have scaled our data governance beautifully. Instead of applying policies table-by-table, we tag columns (PII, sensitive financial data, etc.), and policies auto-apply across hundreds of tables. It's governance that actually keeps up with our data growth.
It has these layers of operational intelligence that reduce busywork and let teams focus on actual analytics rather than infrastructure babysitting.
What do you dislike about the product?
The small file problem has been a real headache when I'm working with streaming data sources. Snowflake performs best with larger files (100-250MB compressed), but many of my real-world pipelines generate thousands of tiny files. This causes performance degradation and forcing me to build a separate compaction layer; adding complexity to what should be simple ingestion. UDF performance has been disappointing. Python and Java UDFs are noticeably slower than native SQL functions. For complex transformations, I've found it's often more efficient to process data outside Snowflake and load the results; which somewhat undermines the single-platform value I was hoping for. These aren't dealbreakers for me but they do require thoughtful architectural decisions
What problems is the product solving and how is that benefiting you?
Snowflake is primarily solving infrastructure complexity and scalability challenges in my analytics environment, and the benefits are tangible. My team focuses on building analytics rather than maintaining databases, which has freed up significant engineering time. With secure data sharing, I can provide partners and internal teams access to datasets without creating copies, managing APIs, or building custom access layers. This has dramatically reduced the time from "data request" to "data access" from weeks to hours. The core benefit is speed to insight with less operational overhead. I'm spending more time answering business questions and less time managing database infrastructure, which is exactly what I need from a modern data platform.
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