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 5.7% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 91% of OpenText users who would recommend it.

BigQuery

Read 40 BigQuery reviews

3,084 Views
2,470 Comparison Views

100% willing to recommend

Vertica

Read 86 Vertica reviews

2,263 Views
1,722 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 May 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 7.0%, down from 8.2% compared to the previous year. The mindshare of Vertica is 5.7%, up from 5.3% 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

"The product's most valuable features include its scalability and the ability to handle complex queries on large datasets."

"It's straightforward to set up."

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

"The main thing I like about BigQuery is storage. We did an on-premise BigQuery migration with trillions of records. Usually, we have to deal with insufficient storage on-premises, but in BigQuery, we don't get that because it's like cloud storage, and we can have any number of records. That is one advantage. The next major advantage is the column length. We have some limits on column length on-premises, like 10,000, and we have to design it based on that. However, with BigQuery, we don't need to design the column length at all. It will expand or shrink based on the records it's getting. I can give you a real-life example based on our migration from on-premises to GCP. There was a dimension table with a general number of records, and when we queried that on-premises, like in Apache Spark or Teradata, it took around half an hour to get those records. In BigQuery, it was instant. As it's very fast, you can get it in two or three minutes. That was very helpful for our engineers. Usually, we have to run a query on-premises and go for a break while waiting for that query to give us the results. It's not the case with BigQuery because it instantly provides results when we run it. So, that makes the work fast, it helps a lot, and it helps save a lot of time. It also has a reasonable performance rate and smart tuning. Suppose we need to perform some joins, BigQuery has a smart tuning option, and it'll tune itself and tell us the best way a query can be done in the backend. To be frank, the performance, reliability, and everything else have improved, even the downtime. Usually, on-premise servers have some downtime, but as BigQuery is multiregional, we have storage in three different locations. So, downtime is also not getting impacted. For example, if the Atlantic ocean location has some downtime, or the server is down, we can use data that is stored in Africa or somewhere else. We have three or four storage locations, and that's the main advantage."

"BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes."

"The setup is simple."

"The feature called calibrating the capacity is valuable."

"I like that we can synch and run a large query. I also like that we can work with a large amount of data. You don't need to work separately, as it's a ready-made solution. It also comes with a built-in machine-learning feature. Once we start inputting the data, it will suggest some things related to the data, and we can come up with nice dashboards and statistics from a vast amount of data."

More BigQuery pros

"The most valuable feature is Vertica's performance and the ease of using the database."

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

"Vertica uses advanced Azure technologies to compress raw data using indexing, allowing a large amount of data to be stored with minimal physical space. Advanced algorithms are employed in data compression."

"The product's initial setup phase is extremely simple."

"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."

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

"We are able to integrate our Vertica data warehouse with Tableau to create numerous reports quickly and efficiently."

"Vertica enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance."

More Vertica pros

Cons

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

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

"With other columnar databases like Snowflake, you can actually increase your VM size or increase your machine size, and you can buy more memory and it will start working faster, but that's not available in BigQuery. You have to actually open a ticket and then follow it up with Google support."

"The solution hinges on Google patterns so continued improvement is important."

"The product’s performance could be much faster."

"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."

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

"There is a good amount of documentation out there, but they're consistently making changes to the platform, and, like, their literature hasn't been updated on some plans."

More BigQuery cons

"It would be great if this were a managed service in AWS."

"In a future release, we would like to have artificial intelligence capabilities like neural networks. Customers are demanding this type of analytics."

"The documentation of Vertica is an area with shortcomings where improvements are required."

"One feature, which has really benefited us, is the scalability offered by Vertica as it has enabled Pythian's clients to manage data with agility."

"They could improve on customer service."

"In my opinion, Vertica's documentation could be improved. Currently, there is not enough documentation available to gain a comprehensive understanding of the platform."

"Limitations in group by projections is where I would like to see an improvement."

"Documentation has become much better, but can always use some improvement."

More Vertica cons

Pricing and Cost Advice

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

"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."

"The pricing appears to be competitive for the intended usage scenarios we have in mind."

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

"The platform is inexpensive."

"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."

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

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

More BigQuery pricing and cost advice

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

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

"From a cost perspective, the software is less than most of its competitors."

"I am aware that we have licensed it, but I have no knowledge of its cost."

"Read the fine print carefully."

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

"Vertica is an expensive tool."

"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

17%

Financial Services Firm

15%

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...

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 20% of the time

Oracle Autonomous Data Warehouse vs BigQuery

Compared 16% 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

Oracle Exadata vs Vertica

Compared 9% of the time

Snowflake vs Vertica

Compared 9% of the time

Amazon Redshift vs Vertica

Compared 7% of the time

More Vertica Competitors

Product Reports

Buyer's Guide

BigQuery

May 2025

Download BigQuery product report

Buyer's Guide

Vertica

April 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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