BigQuery vs Vertica comparison

Google and OpenText are both solutions in the Cloud Data Warehouse category. Google is ranked #3 with an average rating of 8.3, while OpenText is ranked #11 with an average rating of 8.0. Google holds a 6.8% mindshare in CDW, compared to OpenText’s 5.7% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 91% of OpenText users who would recommend it.

BigQuery

Read 41 BigQuery reviews

2,915 Views
1,576 Comparison Views

100% willing to recommend

Vertica

Read 86 Vertica reviews

2,115 Views
1,164 Comparison Views

91% willing to recommend

BigQuery

Vertica

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 18, 2024

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.

To learn more, read our detailed BigQuery vs. Vertica Report (Updated: June 2025).

Buyer's Guide

BigQuery vs. Vertica

June 2025

Download the complete report

Helped 856,873 peers since 2012

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

BigQuery

Ranking in Cloud Data Warehouse

3rd

Average Rating

8.2

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Vertica

Ranking in Cloud Data Warehouse

11th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Warehouse (8th)

Mindshare comparison

As of June 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 6.8%, down from 8.3% compared to the previous year. The mindshare of Vertica is 5.7%, up from 5.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

Luís Silva

Chief Technical Lead at Human Code

Handles large data sets efficiently and offers flexible data management capabilities

The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data. It is kind of difficult to explain, but structured data and the ability to handle large data sets are key features. The data integration capabilities in BigQuery were, in fact, an issue at the beginning. There are two types of integrations. As long as integration is within Google, it is pretty simple. When you start to try to connect external clients to that data, it becomes more complex. It is not related to BigQuery, it is related to Google security model, which is not easy to manage. I would not call it an integration issue of BigQuery, I would call it an integration issue of Google security model.

Read full review

T Venkatesh

Deputy Manager at ICICIBANK Ltd

Processes query faster through multiple systems simultaneously, but it could support different data types

We use the solution for various tasks, including preparing data marts and generating offers. It helps extract data based on rules from the policy team and provides insights to enhance business operations. We also analyze transactions to target customers and improve business performance The…

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"When integrating their system into the cloud-based solutions, we were able to increase their efficiency and overall productivity twice compared with their on-premises option."

"The initial setup is straightforward."

"The setup is simple."

"BigQuery is a powerful tool for managing and analyzing large datasets. The versatility of BigQuery extends to its compatibility with external data visualization tools like Power BI and Tableau. This means you not only get query results but can also seamlessly integrate and visualize your data for better insights."

"The solution's reporting, dashboard, and out-of-the-box capabilities match exactly our requirements."

"What I like most about BigQuery is that it's fast and flexible. Another advantage of BigQuery is that it's easy to learn."

"The most valuable features of this solution, in my opinion, are speed and performance, as well as cost-effectiveness."

"The product’s most valuable feature is its ability to manage the database on the cloud."

More BigQuery pros

"It maximizes cloud economics with Eon Mode by scaling cluster size to meet variable workload demands."

"The fast columnar store database structure allows our query times to be at least 10x faster than on any other database."

"The Vertica architecture means it can process/ingest data in parallel to reporting and analyzing because of its in-memory Write-Optimized Storage sitting alongside the analytics optimized Read-Optimized Storage."

"The performance is very good and the aggregate records are fast."

"I like the projection feature, which increases query performance."

"Allows us to take volumes and process them at a very high speed."

"It maximize cloud economics for mission-critical big data analytical initiatives."

"I don't need any special hardware. I can use commodity hardware, which is nice to have in a commercial solution."

More Vertica pros

Cons

"When I execute a query, the dashboard doesn't always present the output seamlessly. Troubleshooting requires opening each pipeline individually, which is time-consuming."

"It would be helpful if they could provide some dashboards where you can easily view charts and information."

"They could enhance the platform's user accessibility."

"Some of the queries are complex and difficult to understand."

"Sometimes, support specialists might not have enough experience or business understanding, which can be an issue."

"Instead of connecting directly to BigQuery, we connect to GCP, Cloud Run, and then to BigQuery, which is a long process."

"BigQuery can be very expensive if not used properly. Introducing AI tools that would allow you to optimize the data extraction process is an area of serious improvement."

"The processing capability can be an area of improvement."

More BigQuery cons

"Some of our small to medium-sized customers would like to see containerization and flexibility from the deployment standpoint."

"I think they need an easy client so that you can write queries easily, but it's not necessarily a weak point. I think some users would need them."

"They could improve the integration and some of the features in the cloud version."

"Suboptimal projection design causes queries to not scale linearly."

"It's hard to make it slow for a small data volume. For large volumes, it's hard to make it work. It's also hard to make it faster, and to make it scale."

"Whatever's out, the core is not always as great as the engine, especially their first version."

"When it is about to reach the maximum storage capacity, it becomes slow."

"It needs integration with multiple clouds."

More Vertica cons

Pricing and Cost Advice

"The platform is inexpensive."

"Its cost structure operates on a pay-as-you-go model."

"The product operates on a pay-for-use model. Costs include storage and query execution, which can accumulate based on data volume and complexity."

"We are above the free threshold, so we are paying around 40 euros per month for BigQuery."

"One terabyte of data costs $20 to $22 per month for storage on BigQuery and $25 on Snowflake. Snowflake is costlier for one terabyte, but BigQuery charges based on how much data is inserted into the tables. BigQuery charges you based on the amount of data that you handle and not the time in which you handle it. This is why the pricing models are different and it becomes a key consideration in the decision of which platform to use."

"The price could be better. Usually, you need to buy the license for a year. Whenever you want more, you can subscribe to it, and you can use it. Otherwise, you can terminate the license. You can use it daily or monthly, and we use it based on a project's requirements."

"The price is a bit high but the technology is worth it."

"The pricing is adaptable, ensuring that organizations can tailor their usage and costs based on their specific requirements and configurations within the Google Cloud Platform."

More BigQuery pricing and cost advice

"Read the fine print carefully."

"The pricing and licensing depend on the size of your environment and the zone where you want to implement."

"It is fast to purchase through the AWS Marketplace."

"The price could be cheaper and it is best to negotiate the price."

"It's an expensive product"

"It's difficult today to compete with open-source solutions. In these areas, there is a lot of competition and the price of this solution is a bit pricy."

"It's free up to three nodes and 1TB, and then get in contact with their sales guys."

"The pricing for this solution is very reasonable compared to other vendors."

More Vertica pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.

See recommendations

856,873 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Computer Software Company

17%

Financial Services Firm

16%

Manufacturing Company

11%

Retailer

Financial Services Firm

19%

Computer Software Company

18%

Manufacturing Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about BigQuery?

The initial setup process is easy.

See all answers

What is your experience regarding pricing and costs for BigQuery?

I believe the cost of BigQuery is competitive versus the alternatives in the market, but it can become expensive if the tool is not used properly. It is on a per-consumption basis, the billing, so ...

See all answers

What needs improvement with BigQuery?

I have not used BigQuery for AI and machine learning projects myself. I know how to use it, and I can see where it would be useful, but so far, in my projects, I have not included a BigQuery compon...

See all answers

What do you like most about Vertica?

Vertica is easy to use and provides really high performance, stability, and scalability.

See all answers

What is your experience regarding pricing and costs for Vertica?

The solution is relatively cost-effective. Pricing and licensing are reasonable compared to other solutions.

See all answers

What needs improvement with Vertica?

The product could improve by adding support for a wider variety of data types and enhancing features to better compete with other databases.

See all answers

Comparisons

Snowflake vs BigQuery

Compared 18% of the time

Oracle Autonomous Data Warehouse vs BigQuery

Compared 17% of the time

Teradata vs BigQuery

Compared 16% of the time

Apache Hadoop vs BigQuery

Compared 8% of the time

Oracle Exadata vs BigQuery

Compared 8% of the time

More BigQuery Competitors

SQL Server vs Vertica

Compared 14% of the time

Teradata vs Vertica

Compared 12% of the time

Snowflake vs Vertica

Compared 9% of the time

Oracle Exadata vs Vertica

Compared 8% of the time

Amazon Redshift vs Vertica

Compared 6% of the time

More Vertica Competitors

Product Reports

Buyer's Guide

BigQuery

June 2025

Download BigQuery product report

Buyer's Guide

Vertica

May 2025

Download Vertica product report

Also Known As

No data available

Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand

Overview

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.

Google

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:

Efficiency: Vertica provides robust compression and intuitive impressions. This results in users requiring significantly less storage and hardware than other comparable data analytics solutions. The progressive Vertica architecture results in queries that are 10-50 times faster than other platforms while providing more storage data per server.
Integration: Each new iteration of Vertica is tested and certified with the latest ETL and visualization tools. It actively supports Java Database Connectivity (JDBC), Open Database Connectivity (ODBC), and popular SQL providers. All these solutions and most leading BI and visualization tools interact seamlessly, making Vertica overall a very cost-effective solution and solid business investment.
Cloud flexibility: With Vertica, users do not have to get locked into a single cloud vendor. Users are able to take complete advantage of the current infrastructure that is already in place. Vertica seamlessly integrates with popular public clouds, including Google Cloud Platform (GCP), Azure, AWS, Alibaba, VMware clouds, and more. It also provides for easy portability across on-premise and multi-cloud environments and data lakes. Vertica designs a robust flexible platform for running a company’s analytical and computing workloads, which allows applications to run simultaneously on numerous environments in a hybrid cloud infrastructure. Vertica is able to seamlessly use public clouds and private data centers, and it grants the flexibility to switch in an instant.
Security: Vertica offers dynamic end-to-end security with support for partner solutions and industry-standard protocols such as Apache Sentry, AWS IAM, Kerberos, LDAP, and more. Vertica utilizes an intuitive layered security model that provides multiple security authentication authorization mechanisms. Vertica will also maintain an audit trail, natively exported to other security domains for analysis and persistence.

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

OpenText

Sample Customers

Information Not Available

Cerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.

Buyer's Guide

BigQuery vs. Vertica

June 2025

Free Report: BigQuery vs. Vertica

Find out what your peers are saying about BigQuery vs. Vertica and other solutions. Updated: June 2025.

DOWNLOAD NOW

856,873 professionals have used our research since 2012.

See our BigQuery vs. Vertica report.

See our list of best Cloud Data Warehouse vendors.

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.