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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 Hyperion (legacy)

    Score7.5 out of 10
    N/AOracle's Corporate Performance Management suite was acquired from Hyperion in 2007. Hyperion customers are encouraged to migrate to Oracle Fusion Cloud EPM.N/A
    Pricing
    Google BigQueryOracle Hyperion (legacy)
    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 Hyperion (legacy)
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Google BigQueryOracle Hyperion (legacy)
    Considered Both Products
    Google
    No answer on this topic
    Discontinued Products
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    No answers on this topic
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    No answers on this topic
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    42 Answers
    No answers on this topic
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    No answers on this topic
    Features
    Google BigQueryOracle Hyperion (legacy)
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Oracle Hyperion (legacy)
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Oracle Hyperion (legacy)
    -
    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
    Budgeting, Planning, and Forecasting
    Comparison of Budgeting, Planning, and Forecasting features of Google BigQuery and Oracle Hyperion (legacy)
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Hyperion (legacy)
    10.0
    22 Ratings
    8% above category average
    Long-term financial planning00 Ratings10.017 Ratings
    Financial budgeting00 Ratings10.020 Ratings
    Forecasting00 Ratings10.021 Ratings
    Scenario modeling00 Ratings10.016 Ratings
    Management reporting00 Ratings10.021 Ratings
    Analytics and Reporting
    Comparison of Analytics and Reporting features of Google BigQuery and Oracle Hyperion (legacy)
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Hyperion (legacy)
    8.2
    20 Ratings
    9% below category average
    Personalized dashboards00 Ratings8.018 Ratings
    Color-coded scorecards00 Ratings7.115 Ratings
    KPIs00 Ratings9.917 Ratings
    Cost and profitability analysis00 Ratings9.917 Ratings
    Key Performance Indicator setting00 Ratings8.015 Ratings
    Benchmarking with external data00 Ratings6.013 Ratings
    Best Alternatives
    Google BigQueryOracle Hyperion (legacy)
    Small Businesses
    MongoDB Atlas
    Score7.8 out of 10
    No answers on this topic
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    No answers on this topic
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryOracle Hyperion (legacy)
    Likelihood to Recommend
    9.0
    (79 ratings)
    10.0
    (23 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    5.0
    (1 ratings)
    Usability
    6.6
    (6 ratings)
    -
    (0 ratings)
    Availability
    7.3
    (1 ratings)
    -
    (0 ratings)
    Performance
    6.4
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    4.8
    (11 ratings)
    8.0
    (1 ratings)
    Configurability
    6.4
    (1 ratings)
    -
    (0 ratings)
    Contract Terms and Pricing Model
    10.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    7.3
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    7.3
    (1 ratings)
    -
    (0 ratings)
    Professional Services
    8.2
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    Google BigQueryOracle Hyperion (legacy)
    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
    Discontinued Products
    Well suited: For use in multiple offices around the world. I was able to obtain financial reporting data from 5 foreign offices and then consolidate their data with 3 domestic USA offices to prepare a consolidated financial statement. Less Appropriate: Translating the financial value for consulting services could be a bit challenging because that required human interaction and judgement. It would have been great to be able to set up some software to be able to interpret this and let it run for all future project work revenue projection.
    Incentivized
    Read full review
    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
    Read full review
    Discontinued Products
    • This product handles budgeting by Employee and/or Position very well. It is highly flexible and allows Hyperion administrators the ability to develop a planning application that fits a variety of different business needs.
    • It is great at calculating benefits using business rules to automate the population of these fringe costs in the overall budget planning process. This greatly reduces user error.
    • It allows you to seed the operating budget based on changes to key drivers, such as percentage increases, flat dollar increases and more detailed changes using business rules.
    • Allows visibility into the plans for each unit across the organization, rolled up into an overall budget for the campus.
    • It handles the creation of budgets with multiple chartfield segments or dimensions, which most other budgeting systems cannot handle well. It can aggregate these very quickly.
    Incentivized
    Read full review
    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
    Discontinued Products
    • One pain point for us is the consolidation and translation process. Needing to translate the data over and over again is frustrating and there is no visibility into how many users are running a translation. If multiple users attempt to translate the same data set, say goodbye to your performance but you have no way of knowing! (Unless you want to pull up a task audit which is not a very realistic expectation). It has the been the quickest way for us to bring the system to it's knees. The consolidation process performs in direct correlation to the complexity of the calculation/consolidation rules. So, while the product is extremely flexible, you still have to be careful how you design your rules and calculations to make sure that you do it on the smallest subset of data as possible to avoid large processing times. This makes sense, but requires some significant expertise that most organizations do not have in-house.
    • The Hyperion Financial Reporting product is ridiculously outdated and clunky to use. The interface for designing reports is not intuitive, and not easy to modify once a report is built. I think there must be a strategic decision to move away from it and go to something more like Oracle BI because I just can't understand why in the world they don't update the reporting product. It also requires a significant level of expertise to be able to use. Not a great solution at all if you want multiple end-users to create reports in something other than Excel. Nobody except the HFM admin (which I used to be) in our company even touches this module.
    • Another pain point is the amount of IT support that is required to run this thing, and again, specialized knowledge of Hyperion products and how they work is required for IT to adequately support it. This goes for application servers and the Oracle database that the applications are running on.
    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
    Discontinued Products
    We're in the middle of the road because we are not sure that other products on the market fit the bill for what we need yet. Hyperion is expensive and burdensome from an administrator and maintenance standpoint, but it still seems to be the best solution for what we need. Show us an equally capable SaaS consolidation product and we'll talk again.
    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
    Read full review
    Discontinued Products
    No answers on this topic
    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
    Read full review
    Discontinued Products
    No answers on this topic
    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
    Read full review
    Discontinued Products
    No answers on this topic
    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
    Read full review
    Discontinued Products
    The premium support team provides much needed dedicated customer service which we are after for what we have paid for this service. We are satisfied with the service and support and do not have any instance where there was an issue that requires escalation to get the right support team. Though the incidence of major issues that requires the premium support are less, we prefer to keep this as a safety net.
    Incentivized
    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
    Read full review
    Discontinued Products
    I use Oracle Hyperion Enterprise Performance Mangement because the company I work at requires me to use it in the Financial Planning sector as most of their data is stored in it. I am open minded and ready to use other performance management tools created by Oracle if my work permits.
    Incentivized
    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
    Discontinued Products
    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
    Read full review
    Discontinued Products
    No answers on this topic
    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.
    Read full review
    Discontinued Products
    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
    Read full review
    Discontinued Products
    • Oracle Hyperion allows us to automate and consolidate financial data that used to be performed manually in spreadsheets. From that perspective the ROI is huge.
    • Oracle Hyperion functionality is extensive and allows us to perform most functions for planning, consolidating and reporting on our financial data.
    • One negative with Oracle Hyperion is that it is complicated to implement and maintain. It takes expertise at all levels (infrastructure and management) to realize the benefits from it.
    Incentivized
    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.