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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
12th
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 September 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 7.7%, down from 7.9% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.1%, up from 4.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
BigQuery7.7%
Oracle Autonomous Data Warehouse5.1%
Other87.2%
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

"It's similar to a Hadoop cluster, except it's managed by Google."
"The solution is very useful nowadays for keeping a huge number of records."
"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 initial setup process is easy."
"We like the machine learning features and the high-performance database engine."
"BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes."
"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."
"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."
"The solution is used for analytics and it works for our data security needs."
"It is a very stable tool...It is an extremely scalable tool."
"One advantage is that if you already have an Oracle Database, it easily integrates with that."
"Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets."
"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."
"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."
"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system."
"The performance and scalability are awesome."
 

Cons

"There are many tools that you have to use with BigQuery that are different services also provided for by Google. They need to all be integrated into BigQuery to make the solution easier to use."
"The initial setup could be improved making it easier to deploy."
"The process of migrating from Datastore to BigQuery should be improved."
"The price could be better. Compared to competing solutions, BigQuery is expensive. It's only suitable for enterprise customers, not small and medium-sized businesses, as they cannot afford this kind of solution. In the next release, it would be better if they improved their AI bot. Although machine learning and artificial intelligence are doing wonders, there is still a lot of room to enhance them."
"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."
"When it comes to queries or the code being executed in the data warehouse, the management of this code, like integration with the GitHub repository or the GitLab repository, is kind of complicated, and it's not so direct."
"I rate BigQuery six out of 10 for affordability. It could be cheaper."
"The primary hurdle in this migration lies in the initial phase of moving substantial volumes of data to cloud-based platforms."
"We are not satisfied with the technical support. Their understanding is lacking."
"My main suggestion for Oracle is the configuration and key values that come for JSON files. When we create a table, especially if you see in our RedShift or some other stuff, if I create a table on top of a JSON file with multiple array columns or superset columns, those column values create some difficulty in Oracle."
"I would like to see Application Express and Oracle R Enterprise fully supported, and I would like to see Oracle Data Mining supported as a front end."
"Ease of connectivity could be improved."
"An improvement for us would be the inclusion of support for an internal IP, so we could use it directly with the VCN in Oracle Cloud."
"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."
"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."
 

Pricing and Cost Advice

"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."
"The product’s pricing could be more flexible for end users."
"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."
"Its cost structure operates on a pay-as-you-go model."
"The price is a bit high but the technology is worth it."
"The solution is pretty affordable and quite cheap in comparison to PDP or Cloudera."
"Price-wise, I think that is very reasonable."
"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."
"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 solution's cost is reasonable."
"The solution is expensive."
"We pay approximately $70,000 per month. The cost includes maintenance and support."
"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."
"You pay as you go, and you don't pay for services that you don't use."
"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."
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Top Industries

By visitors reading reviews
Computer Software Company
17%
Financial Services Firm
14%
Manufacturing Company
11%
Retailer
7%
Computer Software Company
10%
Financial Services Firm
7%
Manufacturing Company
7%
University
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise9
Large Enterprise20
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise1
Large Enterprise11
 

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: July 2025.
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