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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)

    Microsoft BI (MSBI)

    Score8.5 out of 10
    N/AMicrosoft BI is a business intelligence product used for data analysis and generating reports on server-based data. It features unlimited data analysis capacity with its reporting engine, SQL Server Reporting Services alongside ETL, master data management, and data cleansing.

    $14

    per month per user

    Pricing
    Google BigQueryMicrosoft BI (MSBI)
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Power BI Pro
    $14
    per month per user
    Power BI Premium
    $24
    per month per user
    Offerings
    Pricing Offerings
    Google BigQueryMicrosoft BI (MSBI)
    Free Trial
    YesNo
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Google BigQueryMicrosoft BI (MSBI)
    Considered Both Products
    Google
    No answer on this topic
    Microsoft
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    100%
    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
    15 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    100%
    Happy with the feature set
    15 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
    13 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    100%
    Implementation went as expected
    11 Answers
    Features
    Google BigQueryMicrosoft BI (MSBI)
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Microsoft BI (MSBI)
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Microsoft BI (MSBI)
    -
    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 Microsoft BI (MSBI)
    Feature
    Google BigQuery
    -
    Ratings
    Microsoft BI (MSBI)
    9.0
    53 Ratings
    10% above category average
    Pixel Perfect reports00 Ratings8.546 Ratings
    Customizable dashboards00 Ratings9.653 Ratings
    Report Formatting Templates00 Ratings8.951 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of Google BigQuery and Microsoft BI (MSBI)
    Feature
    Google BigQuery
    -
    Ratings
    Microsoft BI (MSBI)
    8.5
    53 Ratings
    6% above category average
    Drill-down analysis00 Ratings8.548 Ratings
    Formatting capabilities00 Ratings8.253 Ratings
    Integration with R or other statistical packages00 Ratings8.342 Ratings
    Report sharing and collaboration00 Ratings8.953 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of Google BigQuery and Microsoft BI (MSBI)
    Feature
    Google BigQuery
    -
    Ratings
    Microsoft BI (MSBI)
    8.5
    52 Ratings
    3% above category average
    Publish to Web00 Ratings9.348 Ratings
    Publish to PDF00 Ratings9.148 Ratings
    Report Versioning00 Ratings7.444 Ratings
    Report Delivery Scheduling00 Ratings8.547 Ratings
    Delivery to Remote Servers00 Ratings8.426 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of Google BigQuery and Microsoft BI (MSBI)
    Feature
    Google BigQuery
    -
    Ratings
    Microsoft BI (MSBI)
    8.7
    52 Ratings
    9% above category average
    Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.651 Ratings
    Location Analytics / Geographic Visualization00 Ratings8.748 Ratings
    Predictive Analytics00 Ratings7.745 Ratings
    Pattern Recognition and Data Mining00 Ratings8.76 Ratings
    Access Control and Security
    Comparison of Access Control and Security features of Google BigQuery and Microsoft BI (MSBI)
    Feature
    Google BigQuery
    -
    Ratings
    Microsoft BI (MSBI)
    9.3
    53 Ratings
    9% above category average
    Multi-User Support (named login)00 Ratings9.449 Ratings
    Role-Based Security Model00 Ratings9.347 Ratings
    Multiple Access Permission Levels (Create, Read, Delete)00 Ratings8.949 Ratings
    Report-Level Access Control00 Ratings9.36 Ratings
    Single Sign-On (SSO)00 Ratings9.431 Ratings
    Mobile Capabilities
    Comparison of Mobile Capabilities features of Google BigQuery and Microsoft BI (MSBI)
    Feature
    Google BigQuery
    -
    Ratings
    Microsoft BI (MSBI)
    8.0
    42 Ratings
    3% above category average
    Responsive Design for Web Access00 Ratings8.239 Ratings
    Mobile Application00 Ratings8.030 Ratings
    Dashboard / Report / Visualization Interactivity on Mobile00 Ratings7.839 Ratings
    Application Program Interfaces (APIs) / Embedding
    Comparison of Application Program Interfaces (APIs) / Embedding features of Google BigQuery and Microsoft BI (MSBI)
    Feature
    Google BigQuery
    -
    Ratings
    Microsoft BI (MSBI)
    8.5
    24 Ratings
    9% above category average
    REST API00 Ratings9.221 Ratings
    Javascript API00 Ratings8.821 Ratings
    iFrames00 Ratings8.820 Ratings
    Java API00 Ratings8.718 Ratings
    Themeable User Interface (UI)00 Ratings8.021 Ratings
    Customizable Platform (Open Source)00 Ratings7.319 Ratings
    Best Alternatives
    Google BigQueryMicrosoft BI (MSBI)
    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 BigQueryMicrosoft BI (MSBI)
    Likelihood to Recommend
    9.0
    (79 ratings)
    8.9
    (77 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    8.0
    (25 ratings)
    Usability
    6.6
    (6 ratings)
    8.9
    (19 ratings)
    Availability
    7.3
    (1 ratings)
    9.5
    (2 ratings)
    Performance
    6.4
    (1 ratings)
    7.0
    (2 ratings)
    Support Rating
    4.8
    (11 ratings)
    8.9
    (15 ratings)
    In-Person Training
    -
    (0 ratings)
    6.9
    (3 ratings)
    Online Training
    -
    (0 ratings)
    8.5
    (2 ratings)
    Implementation Rating
    -
    (0 ratings)
    9.6
    (7 ratings)
    Configurability
    6.4
    (1 ratings)
    10.0
    (2 ratings)
    Contract Terms and Pricing Model
    10.0
    (1 ratings)
    -
    (0 ratings)
    Data Sharing and Collaboration
    -
    (0 ratings)
    8.5
    (42 ratings)
    Data Sources
    -
    (0 ratings)
    8.4
    (41 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 BigQueryMicrosoft BI (MSBI)
    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
    Microsoft
    Microsoft BI has a lot of features and is a very powerful tool, especially if you have folks on your team that know how to utilize all of its capabilities. To truly unlock all that it can do, it does require people to have a deep understanding of its capabilities. That's where the software really shines. If you are looking for a simpler, more basic reporting tool, there are other programs available that do not require such a steep learning curve.
    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
    Microsoft
    • Comparatively easy to use compared to other data analytics solutions, collaborating with other colleagues on data work is simple.
    • Using Visual Studio for database, ETL, reporting, and analytics development save time and money.
    • Transfer of data from one application to another via Excel and comparison of data attributes between applications
    • Dashboard functionality, as well as Python support, are available, allowing you to add additional charts and graphs.
    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
    Microsoft
    • MSBI designs can work on increasing data processing capabilities enough to handle the huge datasets etc.
    • It would be a lot better if it is a little low on cost.
    • it needs to create opportunities little more than they do regarding customization of some very unique visualization effects
    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
    Microsoft
    Microsoft BI is fundamental to our suite of BI applications. That being said, Northcraft Analytics is focused on delighting our customers, so if the underlying factors of our decision change, we would choose to re-write our BI applications on a different stack. Luckily, mathematics are the fundamental IP of our technology... and is portable across all BI platforms for the foreseeable future.
    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
    Microsoft
    The Microsoft BI tools have great usability for both developers and end users alike. For developers familiar with Visual Studio, there is little learning curve. For those not, the single Visual Studio IDE means not having to learn separate tools for each component. For end-users, the web interface for SSRS is simple to navigate with intuitive controls. For ad-hoc analysis, Excel can connect directly to SSAS and provide a pivot table like experience which is familiar to many users. For database development, there is beginning to be some confusion, as there are now three tool choices (VS, SSMS, Azure Data Studio) for developers. I would like to see Azure Data Studio become the superset of SSMS and eventually supplant it.
    Incentivized
    Read full review
    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
    Microsoft
    The product has been reliable.
    Read full review
    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
    Microsoft
    SQL Server Reporting Services (SSRS) can drag at times. We created two report servers and placed them under an F5 load balancer. This configuration has worked well. We have seen sluggish performance at times due to the Windows Firewall.
    Read full review
    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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    Microsoft
    MSBI natively has a site that allows you to vote on user enhancements and bug fixes. This allows the largest nagging issues to float to the top and the development team can prioritize accordingly. As mentioned earlier, the large community base of MSBI developers assist technical resources in handling technical questions.
    Incentivized
    Read full review
    In-Person Training
    Google
    No answers on this topic
    Microsoft
    This training was more directed toward what the product was capable of rather than actual programming.
    Read full review
    Online Training
    Google
    No answers on this topic
    Microsoft
    I have used on-line training from Microsoft and from Pragmatic Works. I would recommend Pragmatic Works as the best way to get up to speed quickly, and then use the Microsoft on-line training to deep dive into specific features that you need to get depth with.
    Read full review
    Implementation Rating
    Google
    No answers on this topic
    Microsoft
    We are a consulting firm and as such our best resources are always billing on client projects. Our internal implementation has weaknesses, but that's true for any company like ours. My rating is based on the product's ease of implementation.
    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
    Microsoft
    We have used the built in ConnectWise Manager reports and custom reports. The reports provide static data. PowerBI shows us live data we can drill down into and easily adjust parameters. It's much more useful than a static PDF report.
    Incentivized
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    Contract Terms and Pricing Model
    Google
    None so far. Very satisfied with the transparency on contract terms and pricing model.
    Read full review
    Microsoft
    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
    Microsoft
    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
    Microsoft
    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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    Microsoft
    • As a SaaS provider we see being able to provide self-service BI to our client users as a competitive advantage. In fact the MSSQL enabled BI is a contributing factor to many winning RFPs we have done for prospective client organisations.
    • However MSSQL BI requires extensive knowledge and skills to design and develop data warehouses & data models as a foundation to support business analysts and users to interrogate data effectively and efficiently. Often times we find having strong in-house MSSQL expertise is a bless.
    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.