Snowflake goverance & security features are straightforward and easy to use. Users roles are simple to manage, and the platform helps with cloud storage while keeping stored data maintained and organized. The SQL workflow, along with Git repository support, makes it easier to maintain and track tasks within the database. Cortex AI is also helpful for everyday tasks and for wide use across the workplace. Overall, Snowflake supports database cost management and integration needs Review collected by and hosted on G2.com.

Snowflake ML tools are quite complex to use as a beginner but the function and features are quite good as compared to other ML tools like models and experiments Review collected by and hosted on G2.com.

Following 3 new things we are exploring and adopting in POC

Built-in dbt: We can now build and track all our data models directly inside Snowflake. This is great because my team no longer has to set up or maintain separate servers just to run our transformations. Everything happens in one place.

Simple Data Ingestion: We used to pay for extra tools just to move data into our system. With Snowflake’s new built-in connectors, we can bring in data from hundreds of sources easily, which saves us money and cuts down on "tool bloat."

Easy AI Integration: In the past, using AI meant moving data to a separate database, which was a security and infrastructure nightmare. Now, we can run powerful AI models (like Claude) directly on our data within Snowflake’s secure walls. Review collected by and hosted on G2.com.

Frequent UI changes in mid of Project: They change the web interface layouts too often without warning. For example, right in the middle of a major dashboard delivery, my team logged in to find the query history and menu buttons had moved. We ended up losing half a morning just retraining people on where to find basic tools.

poor Errors log management: When external connections break, the system error logs don't give enough detail. Recently, a client's BI tool stopped pulling data, and the log just gave a generic communication error. My engineers spent two days testing network rules and user permissions back-and-forth before realizing it was just a simple API token issue on the other tool's side.New Features without documentation" They release advanced tools too quickly before the documentation is fully ready. We wanted to build a quick prototype using their new Cortex AI search features, but the official setup guides were so thin we had to put the project on hold for two months until other developers posted clear tutorials online. Review collected by and hosted on G2.com.

I use Snowflake alongside Spark and a few custom APIs Data moves smoothly between these systems. The compute scaling is partcularly useful when I’m running heavy queries and I rarely need to manually adjust resources much. Secure data sharing is another standout feature when collaborating with external teams and the governance is solid continues to keep pace as our data grows. Review collected by and hosted on G2.com.

Handling a large number of small files can impact performance, so I sometimes have to preprocess the data before loading it. That adds an extra step to my workflow, but aside that I haven’t run into any major issues. Its almost good. Review collected by and hosted on G2.com.

how easy it makes handling large-scale data without worrying too much about infrastructure. You don’t have to think about provisioning or tuning servers, you just focus on the data and queries.

The separation of compute and storage is a big win Review collected by and hosted on G2.com.

cost visibility and control. It’s very easy to spin up warehouses and run queries, but if you’re not careful, costs can grow quickly without it being obvious in real time.Also, for smaller or simpler use cases, it can feel like overkill. Review collected by and hosted on G2.com.

I find Snowflake pretty easy to use, which is a big plus for me. I also like that it has many different levels of permissions, which really helps to store data securely and ensure that only stakeholders can see it. I haven't encountered any issues with the data workload it can manage so far and the integrations with other systems like Airtable, Salesforce, Jotforms, etc work fine. Review collected by and hosted on G2.com.

Sometimes it is a bit hard to understand the correlation or relationships between data inputs. I also believe that it's quite expensive Review collected by and hosted on G2.com.

Snowflake pull data from APIs, cloud storage and security tools into snowflake and setup wasn’t complex. Querery performance has been consistent, even during peak hours. I also appreciate the more advanced features and the fact that multiple teams can work at the same time without running into conflicts. Review collected by and hosted on G2.com.

No problem so far. It helps bring together app data with easy logs and alerts, which makes it easier to track behavior and fastest generate reports to snowflake, it has been a secure and realiable platform for us. Review collected by and hosted on G2.com.

I really like Snowflake's elastic scaling; it's my favorite part. We can run huge queries without managing servers, and it pauses automatically, so we only pay for what we use. The data sharing feature also works great. Sharing live data securely with partners avoids copying and keeps everyone synced on one version of the truth. Snowflake integrates well with the common stack; we use dbt for transformations, Airflow for orchestration, Looker and Tableau for BI, and Python for data science work. We moved from Redshift to Snowflake, which made scaling easier and separated storage from compute, cutting a lot of the cluster management headaches we had before. The setup was quick for the basics, and we had a warehouse running and data loading in under an hour. Review collected by and hosted on G2.com.

Cost can spike if queries aren't optimized, since you pay per compute second. The UI for permissions and roles is also clunky and takes time to get right. Review collected by and hosted on G2.com.

I started my journey with Snowflake as a Data Quality and Governance Engineer. What I appreciate most is the simplicity of the tool and I love how easy it is to access and immediately get started with my work. Lately, I've been using the Snowflake Intelligence for Reporting and it has improved a lot of the work we deliver. With the improved logs and features in Snowsight UI, I am able to pay more attention to the details and artifacts that Data Engineers need in their everyday work. Snowflake is the primary platform where our data is stored, processed and prepared for further business requirements. Review collected by and hosted on G2.com.

Nothing specific to call out, but I’d really like to see more collaboration between Snowflake and GitHub. Version control with third-party libraries does work, but I’d still prefer a more direct collab and tighter integration. Review collected by and hosted on G2.com.

I like Snowflake for its very fast query performance and good integration with ETL and BI tools. I also enjoy the secure data sharing capabilities across teams and projects. It supports semi-structured data like JSON, which makes data ingestion easier from APIs and applications. Auto-scaling is a big plus, saving time because we don't need to manually manage servers during high workloads. The ability to seamlessly scale up or down based on data load is crucial and Snowflake excels in this. It works well with major cloud platforms like AWS, Azure, and GCP. I appreciate its high performance for SQL queries and analytics, which helps business teams get reports quickly for decision-making. Its strong support for analytics and reporting workloads is impressive, and I find it a very good choice for large-scale data processing. Review collected by and hosted on G2.com.

One challenge with Snowflake is cost management. Some areas that could be improved include better cost optimization and monitoring features and improved real-time streaming support for some use cases. There's also a high dependence on cloud connectivity. Specific difficulties in cost management include virtual warehouses that may keep running even when no queries are executing, difficulty in identifying which queries or users are causing high costs, and heavy queries consuming more compute credits. Review collected by and hosted on G2.com.

When I was in my previous company I have been using this tool. The best part about Snowflake is that the storage and compute are completely separate. In my daily workflow, this means our data science team can run massive, heavy queries at the exact same time our business analysts are running their daily dashboards, and absolutely nothing slows down. I also love the Zero-Copy Cloning feature. It lets me create a replica of our production data for testing in just a few seconds without wasting time or storage costs. Review collected by and hosted on G2.com.

While the auto-scaling is great, you have to be really careful with setting up warehouse timeouts. If an analyst accidentally leaves a massive virtual warehouse running or sets the auto-suspend time too high, it can rack up unexpected compute costs very quickly. It requires strict monitoring. Review collected by and hosted on G2.com.