BigQuery vs Vertica comparison

Google and OpenText are both solutions in the Cloud Data Warehouse category. Google is ranked #4 with an average rating of 8.3, while OpenText is ranked #11 with an average rating of 8.0. Google holds a 7.0% mindshare in CDW, compared to OpenText’s 5.6% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 91% of OpenText users who would recommend it.

BigQuery

Read 40 BigQuery reviews

3,303 Views
2,698 Comparison Views

100% willing to recommend

Vertica

Read 86 Vertica reviews

2,392 Views
1,821 Comparison Views

91% willing to recommend

BigQuery

Vertica

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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: April 2025).

Buyer's Guide

BigQuery vs. Vertica

April 2025

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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

4th

Average Rating

8.2

Reviews Sentiment

7.3

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 (5th)

Mindshare comparison

As of April 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 7.0%, down from 8.0% compared to the previous year. The mindshare of Vertica is 5.6%, up from 5.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

VikashKumar1

Tech lead at Ford Motor Company

Easy to maintain and provides high availability

Since I used BigQuery over the GCP cloud environment, I'm not sure whether we can go through internal IDEAs like IntelliJ or DBeaver that we use to connect with databases. Instead of connecting directly to BigQuery, we connect to GCP, Cloud Run, and then to BigQuery, which is a long process. Sometimes, we face some issues, bugs, and defects. We must first connect with a VPN to check data issues while working from home. Then, it allows you to connect to the cloud. After logging into the cloud, it searches for the service we are looking for, and then we go to BigQuery. This is a long process. After that, we analyze the issues in a table. Instead, it would be very helpful if it could provide a tool that we can install on our MacBook or Windows system. Once we open this tool, we can connect directly to the BigQuery server and easily perform tasks.

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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…

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Quotes from Members

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

Pros

"It stands out in efficiently handling internal actions without the need for manual intervention in tasks like building cubes and defining final dimensions."

"BigQuery's querying capabilities are very optimized for large datasets."

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

"BigQuery allows for very fast access, and it is efficient in handling large datasets compared to other SQL databases."

"One of the most significant advantages lies in the decoupling of storage and compute which allows to independently scale storage and compute resources, with the added benefit of extremely cost-effective storage akin to object storage solutions."

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

"BigQuery can be used for any type of company. It has the capability of building applications and storing data. It can be used for OLTP or OLAP. It has many other products within the Google space."

More BigQuery pros

"The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful."

"Vertica is a great product because customers can compress and code data. The infrastructure that data warehouse solutions need is a commodity server so that customers don't have to invest in infrastructure."

"Any novice user can tune vertical queries with minimal training (or no training at all)."

"Partition and join back to node are easy and simple for DBAs."

"DBAs don’t need to add a partition every month/quarter like with other DBs."

"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."

"Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data."

"Vertica is a columnar database where the query performance is extremely fast and it can be used for real-time integrations for API and other applications. The solution requires zero maintenance which is helpful."

More Vertica pros

Cons

"I noticed recently it's more expensive now."

"The price could be better. Compared to competing solutions, BigQuery is expensive. It's only suitable for enterprise customers, not small and medium-sized businesses, as they cannot afford this kind of solution. In the next release, it would be better if they improved their AI bot. Although machine learning and artificial intelligence are doing wonders, there is still a lot of room to enhance them."

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

"When I execute a query, the dashboard doesn't always present the output seamlessly."

"The process of migrating from Datastore to BigQuery should be improved."

"We'd like to have more integrations with other technologies."

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

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

More BigQuery cons

"I have found that coding support could be simplified."

"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."

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

"It should provide a GUI interface for data management and tuning."

"Vertica seems to scale well, except for one use case where you are on a multi-node cluster. For example, if you had a nine-node cluster, one node goes down, then the eight nodes don't scale, because the absence of the node is very apparent, which is a problem. If you have nine nodes or multiple nodes, the whole idea is that if one of those nodes goes down, then you should not see an impact on the system if you have enough capacity. Even though we have enough capacity, you can still see the impact of the one node going down."

"Vertica can improve automation and documentation. Additionally, the solution can be simplified."

"Performance of management of metadata layer (database catalog) needs improvement. We still have to have smaller customers on PostgreSQL; Vertica cannot manage thousands of schemata."

More Vertica cons

Pricing and Cost Advice

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

"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."

"1 TB is free of cost monthly. If you use more than 1 TB a month, then you need to pay 5 dollars extra for each TB."

"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."

"I have tried my own setup using my Gmail ID, and I think it had a $300 limit for free for a new user. That's what Google is offering, and we can register and create a project."

"Price-wise, I think that is very reasonable."

"The tool has competitive pricing."

"The pricing is good and there are no additional costs involved."

More BigQuery pricing and cost advice

"Read the fine print carefully."

"Vertica is an expensive tool."

"The solution is free and we pay for the storage."

"The price is reasonable. We use a pay per license model. Firstly, you need to buy a license. After that, you mainly pay the annual support fee of around 20% or 25%. I think their prices are quite reasonable."

"It's an expensive product"

"The price of Vertica is less expensive than some competitors, such as Teradata."

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

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

More Vertica pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

18%

Financial Services Firm

14%

Manufacturing Company

11%

Retailer

Financial Services Firm

19%

Computer Software Company

18%

Manufacturing Company

Real Estate/Law Firm

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?

The price is perceived as expensive, rated at eight out of ten in terms of costliness. Still, it offers significant cost savings.

See all answers

What needs improvement with BigQuery?

When I open many of the Google Cloud products, I am in an environment that I do not feel familiar with; it is a little overwhelming. In general, if I know SQL and start playing around, it will star...

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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 25% of the time

Oracle Autonomous Data Warehouse vs BigQuery

Compared 16% of the time

Teradata vs BigQuery

Compared 15% of the time

Apache Hadoop vs BigQuery

Compared 7% of the time

Oracle Exadata vs BigQuery

Compared 7% 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 10% of the time

Oracle Exadata vs Vertica

Compared 8% of the time

Amazon Redshift vs Vertica

Compared 7% of the time

More Vertica Competitors

Product Reports

Buyer's Guide

BigQuery

April 2025

Download BigQuery product report

Buyer's Guide

Vertica

March 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

April 2025

Free Report: BigQuery vs. Vertica

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