BigQuery vs Databricks comparison

Read 91 Databricks reviews

2,200 Views
88 Comparison Views

96% willing to recommend

BigQuery

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between BigQuery and Databricks based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

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

BigQuery vs. Databricks

Download the complete report

Helped 859,129 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:

ROI

Sentiment score

7.4

Organizations experienced improved performance and cost savings after adopting BigQuery, achieving a 75% cost reduction and efficient data management.

Sentiment score

6.5

Databricks enhances efficiency and ROI, offering scalable solutions and cost savings over traditional Hadoop with easy setup.

No quotes available

For more quotes and insights, download the BigQuery report

For a lot of different tasks, including machine learning, it is a nice solution.

For more quotes and insights, download the Databricks report

Senior Data Engineer at a logistics company with 51-200 employees

When it comes to big data processing, I prefer Databricks over other solutions.

IshwarSukheja

Head CEO at bizmetric

Customer Service

Sentiment score

7.2

Customers generally find BigQuery support helpful, but integration challenges and resource availability need improvement despite positive responsiveness.

Sentiment score

7.2

Databricks' support is generally praised for responsiveness, though some note delays, with resources often sufficient for independent problem-solving.

rating the customer support at ten points out of ten

Sr. Team Lead - IT at InfoStretch

I have been self-taught and I have been able to handle all my problems alone.

For more quotes and insights, download the BigQuery report

Chief Technical Lead at Human Code

Whenever we reach out, they respond promptly.

Senior Data Engineer at a logistics company with 51-200 employees

As of now, we are raising issues and they are providing solutions without any problems.

For more quotes and insights, download the Databricks report

Data Platform Architect at KELLANOVA

I rate the technical support as fine because they have levels of technical support available, especially partners who get really good support from Databricks on new features.

Lax Kas

Data Engineer at CRAFT Tech

Scalability Issues

Sentiment score

8.0

BigQuery offers impressive scalability and efficiency for large data, but may be costly and present integration challenges for smaller users.

Sentiment score

7.5

Databricks is praised for its adaptability, scalability, automation features, and performance across industries but needs improved autoscaling control.

It is a 10 out of 10 in terms of scalability.

For more quotes and insights, download the BigQuery report

Chief Technical Lead at Human Code

The scalability is definitely good because we are migrating to the cloud since the computers on the premises or the big database we need are no longer enough.

reviewer2641596

Expert Analyst at a healthcare company with 5,001-10,000 employees

The patches have sometimes caused issues leading to our jobs being paused for about six hours.

Senior Data Engineer at a logistics company with 51-200 employees

Databricks is an easily scalable platform.

For more quotes and insights, download the Databricks report

Data Platform Architect at KELLANOVA

I would rate the scalability of this solution as very high, about nine out of ten.

Lax Kas

Data Engineer at CRAFT Tech

Stability Issues

Sentiment score

8.5

BigQuery is highly stable and reliable for cloud data analytics, efficiently handling large volumes with minor issues.

Sentiment score

7.7

Databricks is highly rated for stability and performance, with occasional minor issues often due to user or external factors.

No quotes available

For more quotes and insights, download the BigQuery report

They release patches that sometimes break our code.

Senior Data Engineer at a logistics company with 51-200 employees

Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.

For more quotes and insights, download the Databricks report

Data Platform Architect at KELLANOVA

Databricks is definitely a very stable product and reliable.

AvivCohen

Data Engineer at Cellebrite

Room For Improvement

BigQuery users face challenges with migration, integration, cost, scaling, user interfaces, and call for better machine learning capabilities.

Databricks should improve visualization, integration, user experience, and scalability, addressing concerns about pricing, error messages, and onboarding.

Troubleshooting requires opening each pipeline individually, which is time-consuming.

Sr. Team Lead - IT at InfoStretch

In general, if I know SQL and start playing around, it will start making sense.

reviewer2641596

Expert Analyst at a healthcare company with 5,001-10,000 employees

BigQuery is already integrating Gemini AI into the data extraction process directly in order to reduce costs.

For more quotes and insights, download the BigQuery report

Chief Technical Lead at Human Code

Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.

For more quotes and insights, download the Databricks report

Senior Data Engineer at a logistics company with 51-200 employees

We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.

Rama Subba Reddy Thavva

Solution Architect at Mercedes-Benz AG

Setup Cost

BigQuery offers flexible, pay-as-you-go pricing based on data usage, with low storage costs and adaptable enterprise plans.

Databricks offers flexible, often expensive pricing, mitigated by cloud deployment and tiered licensing, with varied user cost experiences.

Being able to optimize the queries to data is critical. Otherwise, you could spend a fortune.

Chief Technical Lead at Human Code

The price is perceived as expensive, rated at eight out of ten in terms of costliness.

For more quotes and insights, download the BigQuery report

Sr. Team Lead - IT at InfoStretch

It is not a cheap solution.

For more quotes and insights, download the Databricks report

Data Platform Architect at KELLANOVA

Valuable Features

BigQuery excels in scalability, performance, cost-efficiency, and integration with Google products, making it ideal for complex data analyses.

Databricks offers an intuitive interface for data processing, integrating SQL, Python, and features like Delta Lake and MLflow.

It is really fast because it can process millions of rows in just a matter of one or two seconds.

reviewer2641596

Expert Analyst at a healthcare company with 5,001-10,000 employees

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

Sr. Team Lead - IT at InfoStretch

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.

For more quotes and insights, download the BigQuery report

Chief Technical Lead at Human Code

Databricks' capability to process data in parallel enhances data processing speed.

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.

For more quotes and insights, download the Databricks report

Data Platform Architect at KELLANOVA

The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.

Lax Kas

Data Engineer at CRAFT Tech

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

Databricks

Ranking in Cloud Data Warehouse

8th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Science Platforms (1st), Streaming Analytics (1st)

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 Databricks is 8.9%, up from 4.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

Handles large data sets efficiently and offers flexible data management capabilities

Chief Technical Lead at Human Code

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

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

Read full review

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

859,129 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Computer Software Company

16%

Financial Services Firm

16%

Manufacturing Company

12%

Retailer

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

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.

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 ...

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...

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

Oracle Autonomous Data Warehouse vs BigQuery

Comparisons

Snowflake vs BigQuery

Compared 18% of the time

Compared 17% of the time

Teradata vs BigQuery

Compared 16% of the time

OpenText Analytics Database (Vertica) vs BigQuery

Compared 15% of the time

Apache Hadoop vs BigQuery

Compared 8% of the time

More BigQuery Competitors

Dataiku vs Databricks

Compared 11% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

More Databricks Competitors

Product Reports

BigQuery

Download BigQuery product report

Download Databricks product report

Also Known As

No data available

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

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

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Sample Customers

Information Not Available

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

BigQuery vs. Databricks