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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Google BigQuery

    Score8.8 out of 10
    N/AGoogle'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

    Score7.9 out of 10
    N/AOracle 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 BigQueryOracle 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 BigQueryOracle Analytics
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details—Must contact sales team for pricing.
    More Pricing Information
    Community Pulse
    Google BigQueryOracle Analytics
    Considered Both Products
    Google
    No answer on this topic
    Oracle
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    94%
    Would buy again
    15 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    100%
    Delivers good value for the price
    14 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    100%
    Happy with the feature set
    16 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    42 Answers
    100%
    Lived up to sales and marketing promises
    12 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    100%
    Implementation went as expected
    12 Answers
    Features
    Google BigQueryOracle Analytics
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Oracle Analytics
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Oracle Analytics
    -
    Ratings
    Automatic software patching8.017 Ratings00 Ratings
    Database scalability9.079 Ratings00 Ratings
    Automated backups8.524 Ratings00 Ratings
    Database security provisions8.873 Ratings00 Ratings
    Monitoring and metrics8.675 Ratings00 Ratings
    Automatic host deployment8.013 Ratings00 Ratings
    BI Standard Reporting
    Comparison of BI Standard Reporting features of Google BigQuery and Oracle Analytics
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Analytics
    8.1
    62 Ratings
    1% below category average
    Pixel Perfect reports00 Ratings8.055 Ratings
    Customizable dashboards00 Ratings8.161 Ratings
    Report Formatting Templates00 Ratings8.361 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of Google BigQuery and Oracle Analytics
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Analytics
    8.0
    66 Ratings
    0% below category average
    Drill-down analysis00 Ratings8.464 Ratings
    Formatting capabilities00 Ratings8.265 Ratings
    Integration with R or other statistical packages00 Ratings7.145 Ratings
    Report sharing and collaboration00 Ratings8.162 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of Google BigQuery and Oracle Analytics
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Analytics
    7.8
    63 Ratings
    5% below category average
    Publish to Web00 Ratings7.755 Ratings
    Publish to PDF00 Ratings7.762 Ratings
    Report Versioning00 Ratings7.753 Ratings
    Report Delivery Scheduling00 Ratings7.958 Ratings
    Delivery to Remote Servers00 Ratings7.938 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of Google BigQuery and Oracle Analytics
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Analytics
    7.8
    61 Ratings
    2% below category average
    Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings7.559 Ratings
    Location Analytics / Geographic Visualization00 Ratings7.552 Ratings
    Predictive Analytics00 Ratings7.747 Ratings
    Pattern Recognition and Data Mining00 Ratings8.63 Ratings
    Access Control and Security
    Comparison of Access Control and Security features of Google BigQuery and Oracle Analytics
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Analytics
    8.4
    61 Ratings
    1% below category average
    Multi-User Support (named login)00 Ratings8.160 Ratings
    Role-Based Security Model00 Ratings8.160 Ratings
    Multiple Access Permission Levels (Create, Read, Delete)00 Ratings8.560 Ratings
    Report-Level Access Control00 Ratings8.54 Ratings
    Single Sign-On (SSO)00 Ratings8.641 Ratings
    Mobile Capabilities
    Comparison of Mobile Capabilities features of Google BigQuery and Oracle Analytics
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Analytics
    8.0
    48 Ratings
    4% above category average
    Responsive Design for Web Access00 Ratings8.046 Ratings
    Mobile Application00 Ratings8.033 Ratings
    Dashboard / Report / Visualization Interactivity on Mobile00 Ratings8.044 Ratings
    Application Program Interfaces (APIs) / Embedding
    Comparison of Application Program Interfaces (APIs) / Embedding features of Google BigQuery and Oracle Analytics
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Analytics
    7.9
    36 Ratings
    2% above category average
    REST API00 Ratings8.231 Ratings
    Javascript API00 Ratings7.930 Ratings
    iFrames00 Ratings8.223 Ratings
    Java API00 Ratings7.931 Ratings
    Themeable User Interface (UI)00 Ratings7.531 Ratings
    Customizable Platform (Open Source)00 Ratings7.924 Ratings
    Best Alternatives
    Google BigQueryOracle Analytics
    Small Businesses
    MongoDB Atlas
    Score7.8 out of 10
    Cyfe
    Score4 out of 10
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    Qlik Cloud Analytics (Qlik Sense)
    Score8.1 out of 10
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    Sisense
    Score6.9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryOracle Analytics
    Likelihood to Recommend
    9.0
    (79 ratings)
    8.1
    (76 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    9.1
    (8 ratings)
    Usability
    6.6
    (6 ratings)
    8.2
    (6 ratings)
    Availability
    7.3
    (1 ratings)
    9.1
    (1 ratings)
    Performance
    6.4
    (1 ratings)
    9.1
    (1 ratings)
    Support Rating
    4.8
    (11 ratings)
    9.1
    (4 ratings)
    In-Person Training
    -
    (0 ratings)
    9.0
    (1 ratings)
    Online Training
    -
    (0 ratings)
    9.1
    (1 ratings)
    Implementation Rating
    -
    (0 ratings)
    9.1
    (3 ratings)
    Configurability
    6.4
    (1 ratings)
    9.1
    (1 ratings)
    Contract Terms and Pricing Model
    10.0
    (1 ratings)
    -
    (0 ratings)
    Data Sharing and Collaboration
    -
    (0 ratings)
    9.2
    (57 ratings)
    Data Sources
    -
    (0 ratings)
    8.1
    (57 ratings)
    Ease of integration
    7.3
    (1 ratings)
    8.2
    (1 ratings)
    Product Scalability
    7.3
    (1 ratings)
    9.1
    (1 ratings)
    Professional Services
    8.2
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    Google BigQueryOracle Analytics
    Likelihood to Recommend
    Google
    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).
    Incentivized
    Read full review
    Oracle
    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.
    Incentivized
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    Pros
    Google
    • Realtime integration with Google Sheets.
    • 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.
    Incentivized
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    Oracle
    • 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.
    Incentivized
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    Cons
    Google
    • 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.
    Incentivized
    Read full review
    Oracle
    • More AI but with human back up.
    • Less mumbo jumbo so even IT guys/gals can more easily work.
    • More statistics (math) and orientation for those not familiar with it.
    • More live as well as virtual (live) show casing of real situations in business.
    Incentivized
    Read full review
    Likelihood to Renew
    Google
    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.
    Incentivized
    Read full review
    Oracle
    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.
    Read full review
    Usability
    Google
    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.
    Incentivized
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    Oracle
    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.
    Incentivized
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    Reliability and Availability
    Google
    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.
    Incentivized
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    Oracle
    No problems, it's that simple.
    Incentivized
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    Performance
    Google
    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.
    Incentivized
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    Oracle
    Other than anomalies or expected quirks, there were never any earth-shattering delays.
    Incentivized
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    Support Rating
    Google
    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.
    Incentivized
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    Oracle
    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.
    Incentivized
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    In-Person Training
    Google
    No answers on this topic
    Oracle
    Oracle University offers very in-depth training.
    Read full review
    Online Training
    Google
    No answers on this topic
    Oracle
    It was a private training site.
    Incentivized
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    Implementation Rating
    Google
    No answers on this topic
    Oracle
    A properly implemented Endeca solution performs extremely well on the largest of datasets and it positions your organization to immediately achieve your ROI.
    Read full review
    Alternatives Considered
    Google
    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.
    Incentivized
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    Oracle
    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.
    Read full review
    Contract Terms and Pricing Model
    Google
    None so far. Very satisfied with the transparency on contract terms and pricing model.
    Read full review
    Oracle
    No answers on this topic
    Scalability
    Google
    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.
    Incentivized
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    Oracle
    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.
    Incentivized
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    Professional Services
    Google
    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.
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    Oracle
    No answers on this topic
    Return on Investment
    Google
    • 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.
    Incentivized
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    Oracle
    • 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.
    Read full review
    ScreenShots

    Google BigQuery Screenshots

    Screenshot of Migrating data warehouses to BigQuery - Features a streamlined migration path from Netezza, Oracle, Redshift, Teradata, or Snowflake to BigQuery using the fully managed BigQuery Migration Service.Screenshot of bringing any data into BigQuery - Data files can be uploaded from local sources, Google Drive, or Cloud Storage buckets, using BigQuery Data Transfer Service (DTS), Cloud Data Fusion plugins, by replicating data from relational databases with Datastream for BigQuery, or by leveraging Google's data integration partnerships.Screenshot of generative AI use cases with BigQuery and Gemini models - Data pipelines that blend structured data, unstructured data and generative AI models together can be built to create a new class of analytical applications. BigQuery integrates with Gemini 1.0 Pro using Vertex AI. The Gemini 1.0 Pro model is designed for higher input/output scale and better result quality across a wide range of tasks like text summarization and sentiment analysis. It can be accessed using simple SQL statements or BigQuery’s embedded DataFrame API from right inside the BigQuery console.Screenshot of insights derived from images, documents, and audio files, combined with structured data - Unstructured data represents a large portion of untapped enterprise data. However, it can be challenging to interpret, making it difficult to extract meaningful insights from it. Leveraging the power of BigLake, users can derive insights from images, documents, and audio files using a broad range of AI models including Vertex AI’s vision, document processing, and speech-to-text APIs, open-source TensorFlow Hub models, or custom models.Screenshot of event-driven analysis - Built-in streaming capabilities automatically ingest streaming data and make it immediately available to query. This allows users to make business decisions based on the freshest data. Or Dataflow can be used to enable simplified streaming data pipelines.Screenshot of predicting business outcomes AI/ML - Predictive analytics can be used to streamline operations, boost revenue, and mitigate risk. BigQuery ML democratizes the use of ML by empowering data analysts to build and run models using existing business intelligence tools and spreadsheets.