Snowflake AI Data Cloud
SnowflakeExternal reviews
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Consistent High-Performance Queries for High-Volume Data in Snowflake
What do you like best about the product?
Snowflake we process a high volume of sensor and log data, and snowflake keep queries performance stays consistent even when we’re running with heavy joins. That said the pricing model can feel a bit complex to understand at first, especially when you’re getting started. Writing SQL feels straightforward, and the UI is easy enough to navigate without much training. It integrates well with python scripts, Spark jobs, and even lightweight tools like Zapier for automation task, which makes it easier to fit into our existing workflows.
What do you dislike about the product?
Python based processing inside snowflake isn’t always as fast as expect. Because of that, I sometimes run transformations externally first, then load the processed results back into snowflake.
What problems is the product solving and how is that benefiting you?
Snowflake helps consolidate both raw and processed data into single system, this cuts down the time we spend switching between tools and improves turnaround time for analysis. We can scale resources up or down as needed and we’re able to run multiple workloads in parallel without running into performance issues.
Faster Queries and Seamless Secure Data Sharing with Snowflake
What do you like best about the product?
Handling large voulmes of inspection data in Snowflake used to feel slow for us, but it handles that workload much better now. Queries that previously took minutes are completing far faster, which has made our day to day analysis noticeably smoother. I also appreciate the secure data sharing features, since we can share datasets with extral vendors aithout having to create duplicates or maintain extra copies. On to of that, Snowflake integrations with tools like Salesforce and Zapier have been useful for keeping data in sync across systems.
What do you dislike about the product?
In my experience, Python user defined functions tend to be slower than SQL based operations. SO when we have heavier transformations to do in Snowflake, we’all sometimes run that processing outside of Snowflake first and then load the transformed results back in.
What problems is the product solving and how is that benefiting you?
Snowflake helps us maintain a single consistent version of high quality data across teams. This reduces confusion and makes sure everyone is working fron the same numbers, which keeps our reporting aligned.
Smooth Data Movement, Effortless Scaling, and Strong Secure Sharing
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
It centralizes data pipelines and helps cut down processing delays. I can run analyses more fastest without having to worry about backend limitations, even when we’re handling data masking and integration to support third party business needs.
Fast, Scalable, Low-Maintenance Data Warehouse with Smooth Sharing and Integrations
What do you like best about the product?
Ease of use / low maintenance – no infrastructure to manage, which is a big relief compared to traditional data warehouses.
Separation of storage and compute – lets you scale performance independently and avoid resource contention.
Performance & scalability – fast queries, especially with large datasets.
Concurrency handling – multiple teams can query data at the same time without slowing each other down.
Simple data sharing – sharing datasets across teams or even organizations is unusually smooth.
Pay-as-you-go pricing – you only pay for what you use, which feels efficient (when managed well).
Strong ecosystem & integrations – works well with modern data tools (dbt, BI tools, etc.).
Separation of storage and compute – lets you scale performance independently and avoid resource contention.
Performance & scalability – fast queries, especially with large datasets.
Concurrency handling – multiple teams can query data at the same time without slowing each other down.
Simple data sharing – sharing datasets across teams or even organizations is unusually smooth.
Pay-as-you-go pricing – you only pay for what you use, which feels efficient (when managed well).
Strong ecosystem & integrations – works well with modern data tools (dbt, BI tools, etc.).
What do you dislike about the product?
Semi-structured data isn’t always as smooth as advertised
JSON handling is powerful but can become awkward in complex transformations
Limited control compared to traditional systems
You don’t control the underlying infrastructure
Harder to fine-tune at a low level
Data governance & complexity at scale
Managing roles, permissions, and data access can get messy
Especially painful in large organizations with many teams
JSON handling is powerful but can become awkward in complex transformations
Limited control compared to traditional systems
You don’t control the underlying infrastructure
Harder to fine-tune at a low level
Data governance & complexity at scale
Managing roles, permissions, and data access can get messy
Especially painful in large organizations with many teams
What problems is the product solving and how is that benefiting you?
Snowflake is mainly solving problems around scaling, managing, and accessing data efficiently in the cloud—and the benefits usually show up in day-to-day productivity and decision-making.
Excellent for Storing and Working with Massive Data Fast
What do you like best about the product?
It is very useful when you need to store very huge amounts of data and work with it quickly
What do you dislike about the product?
Its AI agentic tools are still too naive and not that helpful
What problems is the product solving and how is that benefiting you?
We use it to store many of our datatables, specially the biggest ones and to access them quickly
Snowflake Makes Multi-Source Data Integration and Reporting Easy
What do you like best about the product?
In my current role, I work with data from a range of sources, including AWS S3 and various APIs and Snowflake manages the ingestion easy process. When its paired with tools like Power BI, it also makes reporting straightforward for business teams. We’re able to integrate our Google Cloud environment with the platform as well, which helps simplify daily data management. I Particularly that clonning tables doesn’t duplicate storage, since it saves time and effort when I’m testing. Query performance has also been consistently reliable in my experience, even when I’m running large joins.
What do you dislike about the product?
Once things I’ve noticed is that if queries aren’t optimized, costz can spike fastest and without much warning. Also, the integration and implementation process isn’t straightforward, which can make getting everything set up more difficult than expected.
What problems is the product solving and how is that benefiting you?
Snowflake solves the problem of pulling all of our scattered data into user dashboard, so I don’t have to keep switching between systems, the data watehouse and our data science and machine learning platforms. I mainly use it to build data models and feed the dashboard and its made our reporting cycles faster, more consistent and easier to manage.
Smooth Daily Data Workflows with Snowflake and Airflow
What do you like best about the product?
We use Snowflake every day to manage data coming from APIs, logs and internal applications. What standa out most is how seamlessly it integrates with tools like Apache Airflow for job scheduling andd AWS S3 for storage. The overall environment feels dependable and thw user friendly interface keeps day to day work simple and efficient. Writing SQl queries is intutive and performance stays consistent even when we’re working with large datasets. Sharing data across teams is also easy and straightforward, which reduces a lot of unnecessary back and forth.
What do you dislike about the product?
Cost tracking needs more attention. If I forget to pause warehouses or if I accidentally run heavy queries, the costs can add up fast. The query history is useful, but when I’m troubleahooting more complex issues, it sometimes doesn’t feel detailed enough to clearly pinpoint what happend and why. Even so, their services still helps us improve the quality of work.
What problems is the product solving and how is that benefiting you?
We used to see delays when processing data overnight, but now our pipelines run much faster. Its been an effective and reliable way to manage our database, support all clients and generate insights from their work. Its also significantly easier to manage everything in Snowflake, rather than juggling multiplw databases and separate scripts.
Snowflake: Powerful, Scalable Analytics with Seamless Integrations
What do you like best about the product?
Snowflake covers almost everything needed I need for analytics within a single dashboard. I’ve worked with integrations like Power BI , Tableau, dbt and even APIs for custom data loads and overall its been a strong data warehousing tool. It supports both structured and semi structured data, including formats like JSON and Parquet, which is useful in real projects. Features such as data sharing, automatic scaling and workload isolation make it easier to collaborate teams without running into conflicts. On top of that, not having to deal with server management is a major plus.
What do you dislike about the product?
There’s a bit of a learing curve when you first start using advanced features like clustering or performance tuning. Keeping costs under control also takes discipline, especially with larger teams. I’ve found that creating multiple roles and assigning the right privileges to each one helps streamline the overall data analysis process.
What problems is the product solving and how is that benefiting you?
It brings data engineering and analytics together, giving us clearer insight into our data. Rather than managing multiple systems, we can rely on Snowflake for storage, transforamtion and querying which saves and reduces complexity throught our worflow.
Maximum Performance with Minimum Maintenance
What do you like best about the product?
The biggest value Snowflake provides is how it removes the 'heavy lifting' of data management. The UI (Snowsight) is incredibly intuitive features like the Performance Explorer and built-in Worksheets mean I rarely have to leave the browser to get meaningful work done.
From a Performance standpoint, the separation of compute and storage is a game-changer; I can run heavy ELT processes without ever lagging our BI dashboards. We’ve also seen a massive boost in AI/Intelligence workflows thanks to Cortex AI and Snowpark, which allow us to run LLM functions and Python logic directly on our data without the security risk of moving it to external servers.
The Integrations are seamless, particularly the Data Marketplace, which has saved us weeks of engineering time by allowing us to 'mount' third-party data instead of building custom APIs. While the Pricing model requires some oversight, the ROI is clear: we’ve replaced three legacy tools with one platform, and the Auto-budgeting features keep costs predictable. Finally, the Onboarding experience was surprisingly smooth; the documentation is so thorough that we rarely need to contact Support, but when we do, they are fast and technically sharp
From a Performance standpoint, the separation of compute and storage is a game-changer; I can run heavy ELT processes without ever lagging our BI dashboards. We’ve also seen a massive boost in AI/Intelligence workflows thanks to Cortex AI and Snowpark, which allow us to run LLM functions and Python logic directly on our data without the security risk of moving it to external servers.
The Integrations are seamless, particularly the Data Marketplace, which has saved us weeks of engineering time by allowing us to 'mount' third-party data instead of building custom APIs. While the Pricing model requires some oversight, the ROI is clear: we’ve replaced three legacy tools with one platform, and the Auto-budgeting features keep costs predictable. Finally, the Onboarding experience was surprisingly smooth; the documentation is so thorough that we rarely need to contact Support, but when we do, they are fast and technically sharp
What do you dislike about the product?
The main challenge I would say is the consumption-based pricing model, which can lead to unpredictable costs if you aren’t extremely diligent with resource monitors and auto-suspend settings. It's very easy for a developer to accidentally leave a large warehouse running or write an unoptimized query that eats up credits faster than expected. Nothing else comes to the mind for now.
What problems is the product solving and how is that benefiting you?
The biggest problem Snowflake solves for me is infrastructure friction. I used to spend way too much time worrying about whether a large query would crash a dashboard or if I had enough 'room' to run a heavy data load. Snowflake handles all that scaling in the background, which lets me move straight to the actual analysis.
It’s also solved the headache of data movement. Between the Marketplace and simple data sharing, I’m no longer building and fixing broken pipelines just to get external data into my environment. For me, the benefit is simple: speed. I can go from a raw dataset to a clean, usable model in a fraction of the time it used to take, simply because the platform stays out of my way and lets me work in whatever language like SQL or Python makes the most sense for the task at hand.
It’s also solved the headache of data movement. Between the Marketplace and simple data sharing, I’m no longer building and fixing broken pipelines just to get external data into my environment. For me, the benefit is simple: speed. I can go from a raw dataset to a clean, usable model in a fraction of the time it used to take, simply because the platform stays out of my way and lets me work in whatever language like SQL or Python makes the most sense for the task at hand.
Snowflake’s Secure Data Sharing and Time Travel Make Daily Analysis Effortless
What do you like best about the product?
I use Snowflake every day to review access logs and keep an eye on user behavior. The secure Data Sharing feature is genuinely one of the most valuable parts of the platform, since it allows us to share datasets across teams without copying anything. I’ve worked with other data platforms before and I still remeber how much time we used to lose to ETL jobs and infrastructure management. Role Based Access Contril (RBAC) is solid as well, especially once its configured correctly. I also appreciate Time Travel, because it makes it simple to jump back and check historical data fastest whenever I need to.
What do you dislike about the product?
RBAC is powerful, but it isn’t very straightforward at first. I had to spend some time testing and adjusting different roles to make sure I wasn’t over permissioning anything. Credit usage is another area you really need to keep an eye on as you go, since its easy to lose track if you’re not paying attention.
What problems is the product solving and how is that benefiting you?
It gives me a single snowflake dashboard where I can track and audit data access, instead of having to jump between multiple systems. It also pulls AI chatbots, machine learning and other tools into one place, which makes it easier for our team to manage data related work within the same portal. This has been particularly useful during internal audits and it also helps us move faster on investigations when something doesn’t look right.
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