BigQuery vs Oracle Autonomous Data Warehouse comparison


Comparison Buyer's Guide

Executive Summary

Categories and Ranking

Ranking in Cloud Data Warehouse
Average Rating
Number of Reviews
Ranking in other categories
No ranking in other categories
Oracle Autonomous Data Ware...
Ranking in Cloud Data Warehouse
Average Rating
Number of Reviews
Ranking in other categories
No ranking in other categories

Mindshare comparison

As of July 2024, in the Cloud Data Warehouse category, the mindshare of BigQuery is 6.3%, down from 8.2% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 8.6%, up from 3.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
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Featured Reviews

Shiva Prasad ELLUR - PeerSpot reviewer
Feb 21, 2023
Good for processing broader and larger data, but lags in query latency
Our organization has a multi-cloud strategy, and we use different data transmission and storage tools depending on the cloud provider. For example, in Azure, we use Databricks for data transmission and Sines for storing data. In AWS, we use DynamoDB for specific use cases. Regarding Google, we use the CDP platform, specifically BigQuery, for their data storage and analysis needs. We have various tools across the different platforms to meet the specific use case needs. We use BigQuery within the Google CDP platform for their data storage and analysis needs. It varies from use case to use case, and we use different platforms accordingly.
Miodrag Milojevic - PeerSpot reviewer
Jul 25, 2023
A tool for data warehousing that offers scalability, stability, and ease of setup
The initial setup of Oracle Autonomous Data Warehouse is easy and basic, especially if one doesn't use the tricks to get Oracle Exadata for use. One doesn't need to know or be involved in technical stuff to do the setup since, at the least, knowledge might be required when working with some external connections, but it is easy because everything can be done within a couple of clicks. The solution is deployed on the cloud. For deployment, you don't need any technical guidance since you can sit, find it on the web, and prepare an Oracle Autonomous Data Warehouse platform by yourself for free for a limited time. The people needed for the deployment and maintenance depend on the implementation one wants. If you do a simple implementation, you don't need anybody for maintenance since everything is on the cloud. You only have to schedule your backup or see if Oracle can schedule a backup, and you don't take care of the backup. For some more sophisticated or technical implementations, you will need staff for some data warehouse except for some parts of the maintenance like backup, patches, or upgrades since these are a few things you take care of in the background, and you only seek help with the maintenance part, if needed.

Quotes from Members

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


"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 has a proprietary way of storing and accessing data in its own data store and is 100% managed without you needing to install anything. There is no need to arrange for any infrastructure to be able to use this solution."
"Even non-coders can review the data in BigQuery."
"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 product’s most valuable feature is its ability to manage the database on the cloud."
"The initial setup is straightforward."
"It's straightforward to set up."
"I like that we can synch and run a large query. I also like that we can work with a large amount of data. You don't need to work separately, as it's a ready-made solution. It also comes with a built-in machine-learning feature. Once we start inputting the data, it will suggest some things related to the data, and we can come up with nice dashboards and statistics from a vast amount of data."
"It is a stable and scalable solution."
"Self-patching and runs machine-learning across its logs all the time"
"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 solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."
"The performance and scalability are awesome."
"The product is easy to use."
"I loved the simplicity of loading the data and simply relying on the self-tuning capabilities of ADW."


"The processing capability can be an area of improvement."
"The initial setup could be improved making it easier to deploy."
"BigQuery should integrate with other tools, such as Cloud Logging and Local Studio, to enhance its capabilities further and enable powerful and innovative analyses."
"As a product, BigQuery still requires a lot of maturity to accommodate other use cases and to be widely acceptable across other organizations."
"Some of the queries are complex and difficult to understand."
"We'd like to see more local data residency."
"The solution hinges on Google patterns so continued improvement is important."
"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."
"They should make the solution more user-friendly."
"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."
"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."
"Ease of connectivity could be improved."
"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."
"It doesn't work well when you have unstructured data or you need online analytics. It is not as nice as Hadoop in these aspects."
"The installation process is complex. Oracle can make the installation process better."
"The solution lacks visibility options."

Pricing and Cost Advice

"BigQuery is inexpensive."
"Its cost structure operates on a pay-as-you-go model."
"The platform is inexpensive."
"BigQuery pricing can increase quickly. It's a high-priced solution."
"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 pricing appears to be competitive for the intended usage scenarios we have in mind."
"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."
"Price-wise, I think that is very 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."
"You pay as you go, and you don't pay for services that you don't use."
"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."
"ROI is high."
"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 cost is perfect with Oracle Universal credit."
"The price depends on the configuration we choose."
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Top Industries

By visitors reading reviews
Computer Software Company
Financial Services Firm
Manufacturing Company
Educational Organization
Financial Services Firm
Computer Software Company
Manufacturing 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 needs improvement with BigQuery?
They could enhance the platform's user accessibility. Currently, the structure of BigQuery leans more towards catering to hard-code developers, making it less user-friendly for data analysts or non...
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?
Cost-wise, it's a solid seven out of ten. A bit costly, but it is a good tool.
What needs improvement with Oracle Autonomous Data Warehouse?
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...

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Sample Customers

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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: May 2024.
791,948 professionals have used our research since 2012.