Executive SummaryUpdated on Dec 28, 2025
OpenText Analytics Database (Vertica) and BigQuery are key players in the data analytics and cloud data warehousing space. BigQuery holds an advantage with its serverless architecture that integrates smoothly with Google's ecosystem offering scalability and machine learning features.
Features: Vertica offers scalability and high performance with its clustering, columnar storage, and projections. It supports concurrent user access and employs an advanced query optimization strategy. BigQuery's serverless design simplifies big data handling without capacity planning and provides seamless integration with Google's ecosystem for efficient SQL querying and machine learning.
Room for Improvement: Vertica could improve workload management and provide more intuitive integration tools, while also refining configuration options for database management. BigQuery could enhance handling of special characters and offer caching support for external tables. Improving integration across platforms and management ease could further benefit BigQuery users.
Ease of Deployment and Customer Service: Vertica supports deployments in private, public, and hybrid clouds with robust on-premises integration, though its technical support varies in quality. BigQuery, primarily operating in the public cloud, is praised for straightforward deployment and solid customer service, though there is room for improved technical support.
Pricing and ROI: Vertica's storage-based pricing can be expensive without careful planning, yet users report a strong ROI due to performance. BigQuery's pay-as-you-go model is generally seen as cost-effective for large-scale data analysis despite potential cost escalation without query optimization, offering significant savings when utilized efficiently.
To learn more, read our detailed
BigQuery vs. OpenText Analytics Database (Vertica) Report (Updated: December 2025).
