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A Quick Guide: BigQuery vs. Snowflake

How you store your data influences how you use your data. Each big data Cloud storage platform has strengths that suit different organizational needs; two of the big players in this area are Google BigQuery and Snowflake. Whether you’re eyeing speed, scalability, or exploring the future with data sharing or separation, this blog explores the benefits of both BigQuery and Snowflake, and how Astrato facilitates data analysis and visualization in each.

Google BigQuery

BigQuery is Google Cloud’s serverless data warehousing solution, processing and analyzing big data with speed and efficiency. Its architecture optimizes processing speed, which is valuable for organizations dealing with real-time data analysis and insights.

The Key Strengths

  • Speed: BigQuery’s unique architecture, utilizing parallel processing across multiple nodes, ensures swift query execution even on massive petabyte-scale datasets in the Google Cloud.
  • Scalability: BigQuery automatically scales resources based on the volume of queries, guaranteeing optimal performance without manual intervention. As a result, BigQuery significantly simplifies infrastructure management.
  • Cost Efficiency: The pay-as-you-go pricing model means you only pay for resources consumed. The separation of storage and compute billing provides unparalleled cost flexibility.

BigQuery x Astrato

For organizations seeking rapid insights, the combination of Astrato and Google BigQuery is a winning strategy. Astrato offers real-time analytics that drives efficient, data-driven decision-making. BigQuery’s speed and scalability means the insights Astrato delivers are more timely and based on as much data as the organization has stored in the Google Cloud Platform. The intuitive interface makes these speedy insights accessible to business users.


Snowflake is a data warehouse solution renowned for its innovative approach to data separation and sharing. As comprehensive data warehouse platform, Snowflake excels at providing secure, scalable, and agile data storage and management. Its architecture is designed to deliver high-performance analytics while maintaining data integrity and separation.

The Key Strengths

  • Data Sharing: Snowflake’s innovative architecture enables seamless data sharing across different accounts, departments, or even external entities. This sharing happens without the need to physically move data.
  • Data Separation: Snowflake’s multi-cluster shared data architecture ensures that diverse workloads can operate independently on the same dataset, optimizing performance and resource utilization.
  • Security Measures: With advanced security features including encryption and granular access controls, Snowflake is the go-to data warehouse solution for industries with stringent compliance requirements.

Snowflake x Astrato

Astrato, a Snowflake technology partner built for the Snowflake data Cloud, simplifies data governance, allowing secure data sharing. Snowflake’s data warehouse architecture ensures workload isolation and efficiency. Stacking the two platforms encourages seamless collaboration while maintaining a tight grip on data control. A prime example of this is Astrato’s ability to surface User-Defined Functions (UDFs) in Snowflake’s Snowpark. The power and flexibility of UDFs offers advanced analytics – Forecasting, Clustering, Sentiment analysis, Machine learning – through Astrato.

Conclusion: BigQuery vs Snowflake

There is no ‘best’ data warehousing option; it depends on specific organizational needs. Both Google BigQuery and Snowflake have respective strengths that are surfaced via Astrato. Specifically, Astrato allows business users to benefit from access to powerful data science analysis and visualization that they would have once relied on dedicated analytics teams for.

Want to get the most out of your data warehouse? Book a demo with an Astrato product expert here!