We compared Snowflake and BigQuery based on our user's reviews in several parameters.
Snowflake is praised for its high performance, scalability, and ease of use, as well as its excellent customer service and reasonable pricing. On the other hand, BigQuery stands out for its robust scalability, efficient performance, seamless integration, and positive ROI. BigQuery users have also highlighted exceptional customer service and transparent pricing, while suggesting areas for improvement in optimization, performance, and integrations.
Features: Snowflake's most valuable features lie in its high performance, scalability, and ease of use. Users appreciate its ability to handle large volumes of data efficiently, with seamless scalability and a user-friendly interface. On the other hand, BigQuery is known for its robust scalability and efficient performance. It also offers seamless integration with other Google Cloud services, flexibility in handling large datasets, and a user-friendly interface.
Pricing and ROI: Snowflake's setup cost is appreciated for its reasonable and competitive pricing, straightforward process, and flexible licensing terms. In comparison, BigQuery boasts a minimal setup cost, enabling a quick and hassle-free implementation process, with a fair and transparent pricing structure. Both products accommodate various user needs and requirements., The user reviews indicate that Snowflake's ROI has been positive. BigQuery's ROI, on the other hand, has led to significant cost savings, improved data analysis capabilities, faster query speed, enhanced efficiency, increased productivity, better decision-making processes, and positive business growth.
Room for Improvement: Snowflake could benefit from enhancements to enhance user experience and functionality. User feedback for BigQuery suggests the need for better optimization and performance when handling larger datasets. Improving query execution time, enhancing reliability and stability, expanding integrations and supporting more data sources, simplifying the user interface, and providing intuitive documentation have been recommended for BigQuery to enhance user experience.
Deployment and customer support: The reviews indicate that for Snowflake, it is necessary to evaluate deployment and setup durations separately, considering different amounts of time spent on each phase, while for BigQuery, both deployment and setup durations should be taken into account depending on the context mentioned by users. No specific user quotes were provided for BigQuery., Snowflake's customer service has received positive feedback for its promptness, effectiveness, and expertise in resolving issues. Customers appreciate their responsiveness and willingness to address concerns. In comparison, BigQuery's customer service is highly praised for its responsiveness, helpfulness, and expertise in explaining and solving queries. Overall, both companies offer exceptional customer service and support.
The summary above is based on 71 interviews we conducted recently with Snowflake and BigQuery users. To access the review's full transcripts, download our report.
"It has a well-structured suite of complimentary tools for data integration and so forth."
"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."
"The initial setup process is easy."
"The product is serverless. We only need to write SQL queries to analyze the data. We need to pay based on the number of queries. The retrieval time is very less. Even if you write large queries, the tool is able to bring back data in a few seconds."
"The initial setup is straightforward."
"There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."
"It stands out in efficiently handling internal actions without the need for manual intervention in tasks like building cubes and defining final dimensions."
"BigQuery excels at structuring data, performing predictions, and conducting insightful analyses and it leverages machine learning and artificial intelligence capabilities, powered by Google's Duarte AI."
"The pricing is reasonable and matches the rest of the market."
"I like the fact that we don't need a DBA. It automatically scales stuff."
"Data Science capabilities are the most valuable feature."
"It's user-friendly. It's SQL-driven. The fact that business can also go to this application and query because they know SQL is the biggest factor."
"Working with Parquet files is support out of the box and it makes large dataset processing much easier."
"Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
"The most valuable feature of Snowflake is it's an all-in-one data warehousing solution."
"The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also."
"Some of the queries are complex and difficult to understand."
"I noticed recently it's more expensive now."
"I rate BigQuery six out of 10 for affordability. It could be cheaper."
"The main challenges are in the areas of performance and cost optimizations."
"I would like to see version-based implementation and a fallback arrangement for data stored in BigQuery storage. These are some features I'm interested in."
"An area for improvement in BigQuery is its UI because it's not working very well. Pricing for the solution is also very high."
"There are some limitations in the query latency compared to what it was three years ago."
"The solution should reduce its pricing."
"If you go with one cloud provider, you can't switch."
"The documentation could improve. They should provide architecture information."
"There is a need for improvements in the documentation, this would allow more people to switch over to this solution."
"There could be better ELT tools that are appropriate for Snowflake. We decided on Matillion and it seemed to be the only one. There need to be better choices, it would be great if Snowflake provided an ELT solution that people could use. Additionally, if there was a pure cloud-based ELT tool it would be useful."
"Portability is a big hurdle right now for our clients. Porting all of your existing SQL ecosystem, such as stored procedures, to Snowflake is a major pain point. Currently, Snowflake stored procedures use JavaScript, but they should support SQL-based stored procedures. It would be a huge advantage if you can write your stored procedures using SQL. It seems that they are working on this feature, and they are yet to release it. I remember seeing some notes saying that they were going to do that in the future, but the sooner this feature comes out, it would be better for Snowflake because there are a lot of clients with whom I'm interacting, and their main hurdle is to take their existing Oracle or SQL Server stored procedures and move them into Snowflake. For this, you need to learn JavaScript and how it works, which is not easy and becomes a little tricky. If it supports SQL-based procedures, then you can just cut-paste the SQL code, run it, and easily fix small issues."
"The cost of the solution could be reduced."
"I see room for improvement when it comes to credit performance. The other thing I'd like to be improved is the warehouse facility."
"There are a lot of features that they need to come up with. A lot of functions are missing in Snowflake, so we have to find a workaround for those. For example, OUTER APPLY is a basic function in SQL Server, but it is not there in Snowflake. So, you have to write complex code for it."
BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 94 reviews. BigQuery is rated 8.2, while Snowflake is rated 8.4. The top reviewer of BigQuery writes "Expandable and easy to set up but needs more local data residency". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". BigQuery is most compared with Teradata, Oracle Autonomous Data Warehouse, Vertica, Apache Hadoop and AWS Lake Formation, whereas Snowflake is most compared with Azure Data Factory, Teradata, Vertica, AWS Lake Formation and Amazon EMR. See our BigQuery vs. Snowflake report.
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