Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Oracle Analytics
Score 7.5 out of 10
N/A
Oracle Analytics is a solution used to visually explore data to create and share compelling stories. Oracle Analytics Cloud is a cloud native service, and Oracle Analytics Server is the on-premise option.
N/A
Pricing
Google BigQuery
Oracle Analytics
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
No answers on this topic
Offerings
Pricing Offerings
Google BigQuery
Oracle Analytics
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Must contact sales team for pricing.
More Pricing Information
Community Pulse
Google BigQuery
Oracle Analytics
Features
Google BigQuery
Oracle Analytics
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google BigQuery
8.5
80 Ratings
0% above category average
Oracle Analytics
-
Ratings
Automatic software patching
8.017 Ratings
00 Ratings
Database scalability
9.179 Ratings
00 Ratings
Automated backups
8.524 Ratings
00 Ratings
Database security provisions
8.773 Ratings
00 Ratings
Monitoring and metrics
8.475 Ratings
00 Ratings
Automatic host deployment
8.013 Ratings
00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Google BigQuery
-
Ratings
Oracle Analytics
8.1
62 Ratings
1% below category average
Pixel Perfect reports
00 Ratings
8.055 Ratings
Customizable dashboards
00 Ratings
8.061 Ratings
Report Formatting Templates
00 Ratings
8.361 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Google BigQuery
-
Ratings
Oracle Analytics
8.0
66 Ratings
0% below category average
Drill-down analysis
00 Ratings
8.564 Ratings
Formatting capabilities
00 Ratings
8.265 Ratings
Integration with R or other statistical packages
00 Ratings
7.345 Ratings
Report sharing and collaboration
00 Ratings
8.262 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Google BigQuery
-
Ratings
Oracle Analytics
7.8
63 Ratings
5% below category average
Publish to Web
00 Ratings
7.755 Ratings
Publish to PDF
00 Ratings
7.762 Ratings
Report Versioning
00 Ratings
7.853 Ratings
Report Delivery Scheduling
00 Ratings
8.058 Ratings
Delivery to Remote Servers
00 Ratings
8.038 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).
Oracle Data Visualization is very effective if used in an enterprise context with huge volumes of data coming from different systems. It supports dashboard and reporting capabilities and is easy to scale. It also allows you to leverage machine learning capabilities to extract hidden data trends. Visualization capabilities are powerful but not so various if compared to other solutions on the market. If you want to present a dashboard to an executive audience and you want to make your dashboards beautiful you must adapt them through PowerPoint.
GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
Seamless integration with other GCP products.
A simple pipeline might look like this:-
GForms -> GSheets -> BigQuery -> Looker
It all links up really well and with ease.
One instance holds many projects.
Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.
Available without of the box connectors for Salesforce and oracle Saas Cloud. This is a huge plus for our business since we don't need another middleware solution just for this sake.
We are able to connect to our on-prem SQL Server database where we have our RMA database and other applications seamlessly without writing custom APIs.
OAC writes directly into ADW which is another advantage for loading Excel files into ADW after dataflow transformations.
OAC allows replication of the database from fusion ERP and lets us create subject areas using the data modeler.
Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.
We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
Scalability and rich integration capabilities. In the future, if we go with Hyperion for the Financial Consolidation and planning purposes -BI integration with Hyperion is going to be much simpler as it has native interface connectivity and even integration capabilities with well known CRM products (Siebel) and ERP Products (Oracle EBS, Peoplesoft, SAP) is going to be easy and straight forward.
I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.
Great, if you are limited to using it along with other Oracle products; sadly, not if you are integrating with other products, which can be a challenge. It is a great product with tons of functionality and great integration with other in-house platforms. Great visuals and customization for data and analytics to provide decision-making data and analysis.
I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.
I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.
BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
Oracle Analytics Support team is very proactive and I have never had a situation where I had to wait for more than a day or two to get my issues resolved. This is a very big help for us and we appreciate Oracle and its team for guaranteeing that experience.
A properly implemented Endeca solution performs extremely well on the largest of datasets and it positions your organization to immediately achieve your ROI.
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
Oracle Analytics Cloud, is one of the most agile and secure data analysis platforms that according to the budget and the amount of use, you can use the resources you need under the cloud. The Oracle brand is also very well known in this field and can meet all the needs of an organization or industry in any sector.
We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.
We have seen the results of this in our initial research and are not surprised that Oracle does this like it does soo many other things in this area, so well.
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
We've used OBIEE (or it's previous named product) for over 13 years and it's still the most used tool for BI by the business.
We moved our largest business system off of Business Object into OBI so we could gain improved performance, reliability, and easier management of metadata.