Vertica and BigQuery are popular competitors in the data analytics and storage sector. BigQuery's serverless architecture and cost model give it an edge in scalability and integration with Google services.
Features: Vertica offers scalable, fast query performance, supporting SQL and real-time data analysis with advanced data storage through projections. Its strong suit is concurrent query processing and data compression. BigQuery, known for its serverless architecture, facilitates easy scaling with a pay-per-use model and integrates seamlessly with other Google services. It supports large-scale data analysis using SQL.
Room for Improvement: Vertica needs enhancements in workload management and optimization for diverse storage, with a need for better documentation and developer tool support. BigQuery requires better handling of special characters, improved query caching for external tables, and regional data compliance. It also requires improvements in cost optimization and migration support from other systems.
Ease of Deployment and Customer Service: Vertica offers deployment flexibility with on-premises and hybrid cloud options, though its technical support feedback is inconsistent. BigQuery's focus is on public cloud deployment, appealing to cloud-native users, but customer support experiences vary, particularly in resolving complex issues.
Pricing and ROI: Vertica employs a data size-based pricing model with flexible options, appreciated for providing a strong ROI, especially in extensive analytical processes. BigQuery's pay-as-you-go model is cost-effective for scaling, but costs may rise if not managed properly, suggesting a need for better enterprise-level cost management.
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.
Vertica is a deploy-anywhere SQL database created for elasticity, speed, and advanced analytics. Vertica enables today’s busy teams to modernize their data warehouses, democratize data and analytics to enable increased access, and deploy analytics in a hybrid cloud environment. Additionally, Vertica merges how companies power their analytics by providing a scalable, open, and elastic database with numerous intuitive features.
In today’s marketplace, organizations are experiencing continued robust growth of data volumes, and citizen data scientists’ broader use of analytics is causing many companies to re-visit and re-examine their systems in order to match the demands of an aggressive marketplace. Analytics are continually swiftly evolving. New data from social media, blogs, IoT sources, data streams, gas and electrical grids, and mobile networks is being constantly gathered in extensive data sets. This presents organizations with a new opportunity to become more data driven, and they must be able to manage the new data growth and identify the trends and sequences that can lead to both improved business opportunities and continued repeat business from their clients.
Vertica Benefits:
Vertica has many valuable key benefits. Some of its most useful benefits include:
Reviews from Real Users
“I am using Vertica for aggregations and dashboards. The most valuable feature of Vertica is the ability to receive large aggregations at a very quick pace. The use case of subclusters is very good.” - Bijal S., Group Chief Technology Officer at Netcore Solutions
“The hardware usage and speed has been the most valuable feature of this solution. It is very fast and has saved us a lot of money.” - Munkhsaikhan B., Project Lead - Digital Transformation Unit at Bodi Electronics LLC
We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.