BigQuery vs Oracle Autonomous Data Warehouse comparison

Google and Oracle are both solutions in the Cloud Data Warehouse category. Google is ranked #3 with an average rating of 8.5, while Oracle is ranked #14 with an average rating of 7.7. Google holds a 7.3% mindshare in CDW, compared to Oracle’s 4.7% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 95% of Oracle users who would recommend it.

BigQuery

Read 43 BigQuery reviews

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3,437 Comparison Views

100% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

2,864 Views
2,119 Comparison Views

95% willing to recommend

BigQuery

Oracle Autonomous Data Ware...

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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: June 2026).

Buyer's Guide

BigQuery vs. Oracle Autonomous Data Warehouse

June 2026

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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

3rd

Average Rating

8.2

Reviews Sentiment

6.9

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 June 2026, in the Cloud Data Warehouse category, the mindshare of BigQuery is 7.3%, up from 6.6% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.7%, up from 4.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
BigQuery	7.3%
Oracle Autonomous Data Warehouse	4.7%
Other	88.0%

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

Kwajah Mohiuddin

Global Head of Architecture at a financial services firm with 1,001-5,000 employees

Provides self-repair features, but the setup is complex

We use the product for online applications. We use it in the financial industry The product has self-repair features. The tool tunes itself. It separates compute from storage. We can scale storage and compute separately. The setup is complex. Oracle is a complex tool. I have been using Oracle…

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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 interface is what I find particularly valuable."

"The setup is simple."

"Even non-coders can review the data in BigQuery."

"The feature called calibrating the capacity is valuable."

"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."

"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."

"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."

"The best features of BigQuery for me are the fact that it's low-code, no-code; you don't have to be a data scientist to really utilize the tool."

More BigQuery pros

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

"The product has self-repair features."

"The integration feature is very good because you can automate protection security automatically, restricting the access of unauthorized people."

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

"Self-patching and runs machine-learning across its logs all the time"

"The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."

"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 is a stable and scalable solution."

More Oracle Autonomous Data Warehouse pros

Cons

"It would be better if BigQuery didn't have huge restrictions. For example, when we migrate from on-premises to on-premise, the data which handles all ebook characters can be handled on-premise. But in BigQuery, we have huge restrictions. If we have some symbols, like a hash or other special characters, it won't accept them. Not in all cases, but it won't accept a few special characters, and when we migrate, we get errors. We need to use Regexp or something similar to replace that with another character. This isn't expected from a high-range technology like BigQuery. It has to adapt all products. For instance, if we have a TV Showroom, the TV symbol will be there in the shop name. Teradata and Apache Spark accept this, but BigQuery won't. This is the primary concern that we had. In the next release, it would be better if the query on the external table also had cache. Right now, we are using a GCS bucket, and in the native table, we have cache. For example, if we query the same table, it won't cost because it will try to fetch the records from the cached result. But when we run queries on the external table a number of times, it won't be cached. That's a major drawback of BigQuery. Only the native table has the cache option, and the external table doesn't. If there is an option to have an external table for cache purposes, it'll be a significant advantage for our organization."

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

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

"I am unsure of the scalability because I need to test it with a bigger project."

"There are areas that could be improved with BigQuery, such as more bolt-on capabilities and the ability to use more bolt-ons for APIs."

"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."

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

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

More BigQuery cons

"One of the major problem is creating custom tablespace. The ADB serverless option doesn't support custom tablespace creation, which could cause issues during on-premise database migration that requires specifically named tablespace. There should be an option to create customized tablespace."

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

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

"The initial setup was pretty complex. It was not easy."

"It is good as data warehouses go, but it is not that good for really big data."

"A lot of the tools that were previously there have now been taken away."

"Ease of connectivity could be improved."

"The solution lacks visibility options."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"The platform is inexpensive."

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

"The solution is pretty affordable and quite cheap in comparison to PDP or Cloudera."

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

"The product’s pricing could be more flexible for end users."

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

"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."

More BigQuery pricing and cost advice

"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."

"The solution's cost is reasonable."

"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."

"Oracle Autonomous Data Warehouse's pricing is fair and reasonable compared to the other cloud vendors."

"The solution is expensive."

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

"ROI is high."

"The price depends on the configuration we choose."

More Oracle Autonomous Data Warehouse pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Outsourcing Company

Manufacturing Company

Media Company

Manufacturing Company

10%

Financial Services Firm

Media Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	13
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?

With what I have seen in BigQuery, I had some response times problems, but then it is an analytical database and not a transactional database, so it comes with eventual consistency. I cannot have e...

See all answers

What is your primary use case for BigQuery?

We are mostly dealing with Google solutions such as BigQuery, NoSQL, SQL analytical database, secrets manager, and most of the serverless infrastructure as well, databases. I run SQL queries on Big...

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 6% of the time

OpenText Analytics Database (Vertica) vs BigQuery

Compared 6% of the time

Dremio vs BigQuery

Compared 5% of the time

More BigQuery Competitors

Snowflake vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 9% of the time

Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse

Compared 9% of the time

Amazon Redshift vs Oracle Autonomous Data Warehouse

Compared 6% of the time

Snowflake Analytics vs Oracle Autonomous Data Warehouse

Compared 5% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

Buyer's Guide

BigQuery

June 2026

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Buyer's Guide

Oracle Autonomous Data Warehouse

June 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

June 2026

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