BigQuery vs Oracle Autonomous Data Warehouse comparison

Why PeerSpot?

Google and Oracle are both solutions in the Cloud Data Warehouse category. Google is ranked #3 with an average rating of 8.7, while Oracle is ranked #14 with an average rating of 6.0. Google holds a 7.4% mindshare in CDW, compared to Oracle’s 4.2% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 95% of Oracle users who would recommend it.

BigQuery

Read 44 BigQuery reviews

5,620 Views
4,665 Comparison Views

100% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

3,381 Views
2,468 Comparison Views

95% willing to recommend

BigQuery

Oracle Autonomous Data Ware...

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 18, 2024

Oracle Autonomous Data Warehouse and BigQuery are competitors in the data warehousing industry. BigQuery seems to have the upper hand due to its extensive analytics capabilities and straightforward usage despite its complex pricing model, while Oracle excels in support and integration capabilities.

Features: Oracle Autonomous Data Warehouse offers automated tuning, easy scalability, and comprehensive data management. Meanwhile, BigQuery stands out with real-time analytics, seamless integration with external tools, and high scalability.

Room for Improvement: Oracle could improve in areas like pricing complexity, integration with non-Oracle environments, and enhancing self-service features for non-technical users. BigQuery might need enhancements in user interface intuitiveness, simplifying complex query management, and offering more in-depth customer support for new users.

Ease of Deployment and Customer Service: Oracle provides a streamlined deployment experience and strong customer support, ensuring quick setup and integration. BigQuery offers a flexible serverless model, beneficial for cloud-native environments, though it may pose challenges for users unfamiliar with Google Cloud.

Pricing and ROI: Oracle has a complex cost setup but promises solid ROI due to its extensive features and support. BigQuery's pricing appears straightforward but gets complex with higher data usage. However, it offers high ROI through its powerful analytics capabilities and scalable cost model, catering to different organizational needs.

To learn more, read our detailed BigQuery vs. Oracle Autonomous Data Warehouse Report (Updated: September 2026).

Buyer's Guide

BigQuery vs. Oracle Autonomous Data Warehouse

September 2026

Download the complete report

Helped 913,806 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

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Oracle Autonomous Data Ware...

Ranking in Cloud Data Warehouse

14th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of September 2026, in the Cloud Data Warehouse category, the mindshare of BigQuery is 7.4%, down from 7.6% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.2%, down from 5.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
BigQuery	7.4%
Oracle Autonomous Data Warehouse	4.2%
Other	88.4%

Cloud Data Warehouse

Featured Reviews

Mikah Sellers

Principal at Sgt Suds

Has supported detailed policy and education analysis with low-code data exploration

I do not use AWS as my main cloud provider within the company and am not currently using it with AWS. My company did not buy it through the AWS Marketplace as I'm the founder of the company. I do not use BigQuery's integration with Google Analytics for custom behavior analysis. I have not utilized the geospatial analysis capabilities with BigQuery as I'm doing mostly human capital work, so geospatial wouldn't make sense. I would rate their service on a scale of one to 10 for Google as ten. I would rate BigQuery as nine out of 10. My experience with the pricing for BigQuery was through a grant from Google. Their pricing is fairly priced and pretty comparable to Microsoft's offering. I haven't had direct experience, but I did look at the pricing of the Microsoft offering and it's pretty similar. I do not deal with Google AI tools such as Vertex.

Read full review

reviewer1297710

IT Administrator at a manufacturing company with 1,001-5,000 employees

Analytics and data security needs are met but optimization requires improvement

We are using Oracle Autonomous Data Warehouse for analytics in my company The solution is used for analytics and it works for our data security needs. We continue to use it with satisfaction. Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not…

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

"The interface is what I find particularly valuable."

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

"The scalability is excellent, as it can handle large datasets and scale up pretty easily as the data volume grows while remaining very reliable with no bugs, glitches, crashes, or freezes."

"As a cloud solution, it's easy to set up."

"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."

"It is stable and reliable; there are no bugs or glitches."

"The most valuable features of BigQuery is that it supports standard SQL and provides good performance."

"BigQuery is a very nice product; it is a good product, scalable, and has high performance."

More BigQuery pros

"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."

"The autonomous database provides several benefits and unmatched performance."

"I like the fact that the solution is self-patching, that it's running machine-learning generally across its logs all the time in order to identify any issues and to self-repair."

"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."

"With Oracle Autonomous Data Warehouse, things are much simpler. Creating a structure, initializing the servers, extending the servers, those are all things that are very, very easy. That's the main reason we use it."

"The solution integrates well with Power BI."

"It is a stable and scalable solution."

"The solution has a self-backup, so you don't need a DBA (database administrator) to do a backup."

More Oracle Autonomous Data Warehouse pros

Cons

"For greater flexibility and ease of use, it would be beneficial if BigQuery offered more third-party add-ons and connectors, particularly for databases that don't have built-in integration options."

"There are some limitations in the query latency compared to what it was three years ago."

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

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

"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."

"I rate BigQuery six out of 10 for affordability. It could be cheaper."

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

"As a product, BigQuery still requires a lot of maturity to accommodate other use cases and to be widely acceptable across other organizations."

More BigQuery cons

"Ease of interconnectivity could be improved by which I mean setting up the VPN access and the like from on-premises to cloud."

"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."

"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."

"Optimization should be better."

"One of the major problem is creating custom tablespace."

"I would like to see an on-premise solution in the future."

"The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora."

"The installation process is complex. Oracle can make the installation process better."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"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 solution's pricing is cheaper compared to other solutions."

"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."

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

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

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

"BigQuery pricing can increase quickly. It's a high-priced solution."

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

More BigQuery pricing and cost advice

"ROI is high."

"In terms of architecture and pricing structure, I feel it is a little bit costly compared to Azure. It's fine compared to RedShift, but compared to Azure, it's a bit pricey when you calculate for one TB storage plus around five hours of reporting with the frequency of 1TB data. The cost adds up, making Oracle a bit expensive."

"The licensing cost of the product can vary since you can integrate it very easily with other products or other cloud products...You pay as you use it, so it is not yearly or monthly payments to be made toward Oracle."

"On a scale from one to ten, where one is a low price and ten is a high price, I rate the pricing an eight."

"We pay approximately $70,000 per month. The cost includes maintenance and support."

"The cost is perfect with Oracle Universal credit."

"Cloud solutions are cheaper, but in the long run, they may not be much cheaper. They certainly have a lower initial cost. The licensing is yearly, and it is based on the size of the hardware and the number of users."

"The solution's cost is reasonable."

More Oracle Autonomous Data Warehouse 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

913,806 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

15%

Outsourcing Company

14%

Media Company

10%

Construction Company

Financial Services Firm

11%

Media Company

10%

Outsourcing Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	15
Midsize Enterprise	10
Large Enterprise	20

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	1
Large Enterprise	11

Questions from the Community

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?

The queries that BigQuery provides are not optimized at a greater level. For simple tasks it is good, but if I want to write complex analyzing queries, it doesn't give the queries up to the mark, s...

See all answers

What is your primary use case for BigQuery?

My main use case for BigQuery is the analysis of our data, creating dashboards from large datasets, and querying the databases that we have, including both structured and unstructured data imported...

See all answers

What is your experience regarding pricing and costs for Oracle Autonomous Data Warehouse?

We pay approximately $70,000 per month. The cost includes maintenance and support.

See all answers

What needs improvement with Oracle Autonomous Data Warehouse?

Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not supported, which is not ideal.

See all answers

What is your primary use case for Oracle Autonomous Data Warehouse?

We are using Oracle Autonomous Data Warehouse for analytics in my company.

See all answers

Comparisons

Snowflake vs BigQuery

Compared 10% of the time

Teradata vs BigQuery

Compared 9% of the time

Snowflake Analytics vs BigQuery

Compared 7% of the time

Databricks vs BigQuery

Compared 6% of the time

Microsoft Azure Synapse Analytics vs BigQuery

Compared 5% of the time

More BigQuery Competitors

Snowflake vs Oracle Autonomous Data Warehouse

Compared 16% of the time

Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse

Compared 10% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 9% of the time

VMware Tanzu Data Solutions vs Oracle Autonomous Data Warehouse

Compared 6% of the time

Amazon Redshift vs Oracle Autonomous Data Warehouse

Compared 6% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

Buyer's Guide

BigQuery

September 2026

Download BigQuery product report

Buyer's Guide

Oracle Autonomous Data Warehouse

September 2026

Download Oracle Autonomous Data Warehouse product report

Also Known As

No data available

Overview

BigQuery is a powerful cloud-based data warehouse offering advanced SQL querying, seamless Google integration, and scalable handling of large datasets. Its serverless architecture and built-in AI capabilities facilitate efficient data processing and insights extraction.

BigQuery provides an efficient data analysis platform with low-latency performance and cost-effective on-demand pricing. Leveraging Google's cloud infrastructure for data storage, it offers robust security and high availability. While it excels in SQL support and caching features, it can improve on user accessibility, integration with diverse tools, and machine learning feature expansion. Making it more accessible for smaller entities through improved cost management and local data compliance is essential. Enhancements in query speed and intuitive interfaces can further optimize performance.

What features are offered by BigQuery?

User-friendly interface: Simplifies data interaction, making complex processes more manageable.
Serverless architecture: Eliminates the need for infrastructure management, improving scalability and efficiency.
Advanced SQL querying: Enables complex data retrieval and manipulation with ease.
Machine learning integration: Facilitates AI-driven insights directly from the platform.
Cost-effective pricing: On-demand pricing helps manage expenses by paying only for used resources.
Seamless Google integration: Works well with familiar Google services for a cohesive experience.
High availability and robust security: Ensures data is secure and accessible when needed.

What benefits should be considered when evaluating BigQuery?

Efficient data processing: Quickly handles large datasets, supporting fast data-driven decision-making.
Scalable infrastructure: Grows capacity alongside business needs without manual infrastructure adjustments.
Enhanced data analysis: SQL support and caching features improve analysis precision and speed.
AI and machine learning capabilities: Enable advanced data insights and predictive analytics.
Integration with existing tools: Ensures smooth workflow transitions with services such as Google Analytics and Tableau.

In industries like healthcare, finance, and marketing, BigQuery is extensively used for data storage, generating reports, and supporting ETL processes. Educational institutions leverage it for analytics, aligning seamlessly with Google Cloud for serverless infrastructure efficiencies.

Google

Oracle Autonomous Data Warehouse is a cloud-based service offering advanced data management capabilities, including automated administration and high performance for analytics tasks. It is ideal for enterprises prioritizing security, easy maintenance, and dynamic scale.

Oracle Autonomous Data Warehouse stands out by offering self-managing capabilities that minimize administrative overhead, allowing organizations to focus on data-driven decision-making. With features such as transparent data encryption, seamless cloud integration, and automated query tuning, it ensures secure and efficient data operations. Its architecture separates compute and storage, enhancing scalability and performance. Despite its setup complexity and higher cost than some competitors, it offers deep integration with Oracle Database, ensuring reliable performance and fast data exchange.

What features define Oracle Autonomous Data Warehouse?

Self-Patching: Automatically updates to ensure security and performance.
Auto-Scaling: Dynamically adjusts resources to meet workload demands.
Query Tuning: Optimizes queries for better performance without user intervention.
Seamless Cloud Integration: Easily connects with Oracle and other cloud applications.
Transparent Data Encryption: Provides secure data handling to meet compliance needs.
Smart Scan: Efficiently processes queries to reduce data retrieval times.

What benefits can be expected from Oracle Autonomous Data Warehouse?

Cost-Effectiveness: Reduces operational costs through automation and serverless operations.
High Security: Ensures data protection with encryption and isolated resources.
Performance Enhancement: High-speed data processing and query response times.
Easy Maintenance: Minimal administrative tasks due to automation.
Scalability: Effortlessly scales resources to accommodate growth.

Oracle Autonomous Data Warehouse is widely used in finance, banking, transport, and manufacturing, supporting data analytics in financial systems, procurement, and student management. It facilitates large-scale transaction processing, offering centralized reporting and dynamic resource allocation, which is crucial for enhancing performance across industries.

Oracle

Sample Customers

Information Not Available

Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank

Buyer's Guide

BigQuery vs. Oracle Autonomous Data Warehouse

September 2026

Free Report: BigQuery vs. Oracle Autonomous Data Warehouse

Find out what your peers are saying about BigQuery vs. Oracle Autonomous Data Warehouse and other solutions. Updated: September 2026.

DOWNLOAD NOW

913,806 professionals have used our research since 2012.

See our BigQuery vs. Oracle Autonomous Data Warehouse 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.