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BigQuery vs Oracle Autonomous Data Warehouse comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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
7.2
Number of Reviews
41
Ranking in other categories
No ranking in other categories
Oracle Autonomous Data Ware...
Ranking in Cloud Data Warehouse
10th
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
19
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 6.5%, down from 8.4% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.0%, up from 4.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

Luís Silva - PeerSpot reviewer
Handles large data sets efficiently and offers flexible data management capabilities
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.
Kwajah Mohiuddin - PeerSpot reviewer
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…

Quotes from Members

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

Pros

"The product is serverless. We only need to write SQL queries to analyze the data. We need to pay based on the number of queries. The retrieval time is very less. Even if you write large queries, the tool is able to bring back data in a few seconds."
"It's pretty stable. It's fast, and it is able to go through large quantities of data pretty quickly."
"It's similar to a Hadoop cluster, except it's managed by Google."
"Its integration with other tools like Atlan through a Google Chrome extension is highly beneficial."
"BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes."
"What I like most about BigQuery is that it's fast and flexible. Another advantage of BigQuery is that it's easy to learn."
"As a cloud solution, it's easy to set up."
"BigQuery allows for very fast access, and it is efficient in handling large datasets compared to other SQL databases."
"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."
"The product has self-repair features."
"The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."
"One advantage is that if you already have an Oracle Database, it easily integrates with that."
"The solution is used for analytics and it works for our data security needs."
"The solution has a self-backup, so you don't need a DBA (database administrator) to do a backup."
"The solution integrates well with Power BI."
"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."
 

Cons

"The solution hinges on Google patterns so continued improvement is important."
"The main challenges are in the areas of performance and cost optimizations."
"They could enhance the platform's user accessibility."
"An area for improvement in BigQuery is its UI because it's not working very well. Pricing for the solution is also very high."
"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 understand that Snowflake has made some improvements on its end to further reduce costs, so I believe BigQuery can catch up."
"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."
"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."
"Optimization should be better."
"Ease of connectivity could be improved."
"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."
"We are not satisfied with the technical support. Their understanding is lacking."
"The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora."
"There is a need for more storage to be allocated, but over a period of time, it becomes impossible to reduce it after using it."
"They should make the solution more user-friendly."
"The solution lacks visibility options."
 

Pricing and Cost Advice

"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."
"The product’s pricing could be more flexible for end users."
"Price-wise, I think that is very reasonable."
"The price is a bit high but the technology is worth it."
"The solution's pricing is cheaper compared to other solutions."
"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 pricing is good and there are no additional costs involved."
"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 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."
"ROI is high."
"The solution is expensive."
"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."
"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 cost is perfect with Oracle Universal credit."
"You pay as you go, and you don't pay for services that you don't use."
"Oracle Autonomous Data Warehouse's pricing is fair and reasonable compared to the other cloud vendors."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Computer Software Company
16%
Manufacturing Company
11%
Retailer
8%
Financial Services Firm
13%
Computer Software Company
10%
Educational Organization
9%
Manufacturing Company
7%
 

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...
What do you like most about Oracle Autonomous Data Warehouse?
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...
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.
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.
 

Overview

 

Sample Customers

Information Not Available
Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank
Find out what your peers are saying about BigQuery vs. Oracle Autonomous Data Warehouse and other solutions. Updated: June 2025.
862,499 professionals have used our research since 2012.