Snowflake and BigQuery are prominent competitors in the data warehousing domain. Snowflake offers superior scalability and flexibility, whereas BigQuery excels in machine learning and cost efficiency.
Features: Snowflake is noted for its scalability using distributed architecture, dynamic node configuration, and multi-formatted data accessibility, which facilitate rapid processing. BigQuery is praised for its speed in handling large datasets, the automatic tuning feature, and robust machine learning integration, providing impressive analytics capabilities.
Room for Improvement: Snowflake should focus on boosting geo-spatial query support, improving connectors, and offering clearer pricing models with better integration tools. BigQuery could enhance its caching for external tables, eliminate character restrictions in data migration, and expand machine learning libraries for broader usability.
Ease of Deployment and Customer Service: Both Snowflake and BigQuery offer robust cloud deployment solutions. Snowflake supports flexible deployment options including hybrid cloud, and is commended for quick and knowledgeable technical support, with room for enhancing SLAs. BigQuery is valued for quick response times and dependable service, making customer experience reliable and consistent.
Pricing and ROI: Snowflake offers a flexible credit-based pricing model that some users find cost-effective but potentially expensive compared to on-premise solutions, with mixed ROI reports focusing on operational efficiency. BigQuery operates with a transparent pay-as-you-go model, making it more predictable and affordable for data processing needs, often delivering a high ROI with its cost-effective storage options.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
Snowflake is very scalable and has a dedicated team constantly improving the product.
Snowflake is very stable, especially when used with AWS.
Cost reduction is one area I would like Snowflake to improve.
Snowflake's pricing is on the higher side.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure. ... You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.
Snowflake is a cloud-based data warehousing solution for storing and processing data, generating reports and dashboards, and as a BI reporting source. It is used for optimizing costs and using financial data, as well as for migrating data from on-premises to the cloud. The solution is often used as a centralized data warehouse, combining data from multiple sources.
Snowflake has helped organizations improve query performance, store and process JSON and XML, consolidate multiple databases into one unified table, power company-wide dashboards, increase productivity, reduce processing time, and have easy maintenance with good technical support.
Its platform is made up of three components:
Snowflake has many valuable vital features. Some of the most useful ones include:
There are many benefits to implementing Snowflake. It helps optimize costs, reduce downtime, improve operational efficiency, and automate data replication for fast recovery, and it is built for high reliability and availability.
Below are quotes from interviews we conducted with users currently using the Snowflake solution:
Sreenivasan R., Director of Data Architecture and Engineering at Decision Minds, says, "Data sharing is a good feature. It is a majorly used feature. The elastic computing is another big feature. Separating computing and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not doing any performance tuning, and the entire burden of performance 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."
A director of business operations at a logistics company mentions, "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."
A Solution Architect at a wholesaler/distributor comments, "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
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