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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Azure Analysis Services

    Score8.6 out of 10
    N/AAzure Analysis Services delivers enterprise-grade BI semantic modeling capabilities with the scale, flexibility, and management benefits of the cloud. Azure Analysis Services helps transform complex data into actionable insights. Azure Analysis Services is built on the analytics engine in Microsoft SQL Server Analysis Services.N/A

    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)

    Pricing
    Azure Analysis ServicesGoogle BigQuery
    Editions & Modules
    No answers on this topic
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Offerings
    Pricing Offerings
    Azure Analysis ServicesGoogle BigQuery
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Azure Analysis ServicesGoogle BigQuery
    Considered Both Products
    Microsoft
    No answer on this topic
    Google
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    9 Answers
    98%
    Would buy again
    64 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    9 Answers
    97%
    Delivers good value for the price
    56 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    9 Answers
    97%
    Happy with the feature set
    63 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    7 Answers
    100%
    Lived up to sales and marketing promises
    42 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    9 Answers
    100%
    Implementation went as expected
    59 Answers
    Features
    Azure Analysis ServicesGoogle BigQuery
    BI Standard Reporting
    Comparison of BI Standard Reporting features of Azure Analysis Services and Google BigQuery
    Feature
    Azure Analysis Services
    8.6
    8 Ratings
    5% above category average
    Google BigQuery
    -
    Ratings
    Pixel Perfect reports8.88 Ratings00 Ratings
    Customizable dashboards8.77 Ratings00 Ratings
    Report Formatting Templates8.58 Ratings00 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of Azure Analysis Services and Google BigQuery
    Feature
    Azure Analysis Services
    8.8
    8 Ratings
    9% above category average
    Google BigQuery
    -
    Ratings
    Drill-down analysis8.96 Ratings00 Ratings
    Formatting capabilities8.77 Ratings00 Ratings
    Integration with R or other statistical packages8.77 Ratings00 Ratings
    Report sharing and collaboration9.08 Ratings00 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of Azure Analysis Services and Google BigQuery
    Feature
    Azure Analysis Services
    9.0
    8 Ratings
    9% above category average
    Google BigQuery
    -
    Ratings
    Publish to Web9.08 Ratings00 Ratings
    Publish to PDF8.97 Ratings00 Ratings
    Report Versioning9.37 Ratings00 Ratings
    Report Delivery Scheduling9.08 Ratings00 Ratings
    Delivery to Remote Servers8.57 Ratings00 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of Azure Analysis Services and Google BigQuery
    Feature
    Azure Analysis Services
    9.0
    7 Ratings
    12% above category average
    Google BigQuery
    -
    Ratings
    Pre-built visualization formats (heatmaps, scatter plots etc.)9.46 Ratings00 Ratings
    Location Analytics / Geographic Visualization9.07 Ratings00 Ratings
    Predictive Analytics8.66 Ratings00 Ratings
    Access Control and Security
    Comparison of Access Control and Security features of Azure Analysis Services and Google BigQuery
    Feature
    Azure Analysis Services
    9.3
    8 Ratings
    9% above category average
    Google BigQuery
    -
    Ratings
    Multi-User Support (named login)9.27 Ratings00 Ratings
    Role-Based Security Model9.38 Ratings00 Ratings
    Multiple Access Permission Levels (Create, Read, Delete)9.38 Ratings00 Ratings
    Single Sign-On (SSO)9.47 Ratings00 Ratings
    Mobile Capabilities
    Comparison of Mobile Capabilities features of Azure Analysis Services and Google BigQuery
    Feature
    Azure Analysis Services
    8.6
    7 Ratings
    11% above category average
    Google BigQuery
    -
    Ratings
    Responsive Design for Web Access8.47 Ratings00 Ratings
    Mobile Application9.33 Ratings00 Ratings
    Dashboard / Report / Visualization Interactivity on Mobile8.35 Ratings00 Ratings
    Application Program Interfaces (APIs) / Embedding
    Comparison of Application Program Interfaces (APIs) / Embedding features of Azure Analysis Services and Google BigQuery
    Feature
    Azure Analysis Services
    8.8
    7 Ratings
    13% above category average
    Google BigQuery
    -
    Ratings
    REST API8.96 Ratings00 Ratings
    Javascript API8.76 Ratings00 Ratings
    iFrames8.85 Ratings00 Ratings
    Java API8.77 Ratings00 Ratings
    Themeable User Interface (UI)8.34 Ratings00 Ratings
    Customizable Platform (Open Source)9.33 Ratings00 Ratings
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Azure Analysis Services and Google BigQuery
    Feature
    Azure Analysis Services
    -
    Ratings
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Automatic software patching00 Ratings8.017 Ratings
    Database scalability00 Ratings9.079 Ratings
    Automated backups00 Ratings8.524 Ratings
    Database security provisions00 Ratings8.873 Ratings
    Monitoring and metrics00 Ratings8.675 Ratings
    Automatic host deployment00 Ratings8.013 Ratings
    Best Alternatives
    Azure Analysis ServicesGoogle BigQuery
    Small Businesses
    Cyfe
    Score4 out of 10
    MongoDB Atlas
    Score7.8 out of 10
    Medium-sized Companies
    Qlik Cloud Analytics (Qlik Sense)
    Score8.1 out of 10
    Azure Database
    Score8.8 out of 10
    Enterprises
    Sisense
    Score6.9 out of 10
    Google Cloud SQL
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Azure Analysis ServicesGoogle BigQuery
    Likelihood to Recommend
    9.0
    (9 ratings)
    9.0
    (79 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    8.1
    (5 ratings)
    Usability
    -
    (0 ratings)
    6.6
    (6 ratings)
    Availability
    -
    (0 ratings)
    7.3
    (1 ratings)
    Performance
    -
    (0 ratings)
    6.4
    (1 ratings)
    Support Rating
    -
    (0 ratings)
    4.8
    (11 ratings)
    Configurability
    -
    (0 ratings)
    6.4
    (1 ratings)
    Contract Terms and Pricing Model
    -
    (0 ratings)
    10.0
    (1 ratings)
    Ease of integration
    -
    (0 ratings)
    7.3
    (1 ratings)
    Product Scalability
    -
    (0 ratings)
    7.3
    (1 ratings)
    Professional Services
    -
    (0 ratings)
    8.2
    (2 ratings)
    User Testimonials
    Azure Analysis ServicesGoogle BigQuery
    Likelihood to Recommend
    Microsoft
    We would have many technical issues and glitches with previous similar providers but found that Azure Analysis Services can simply handle our workload and memory better. I remember we lost an account due to cloud issues not fully saving or corrupting some files. Granted, this is rare with any cloud but haven't had that issue with the same load of memory with Azure Analysis Services.
    Incentivized
    Read full review
    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
    Pros
    Microsoft
    • Providing role based access or we can say privilege based on the role to the user if it is integrated with Azure active directory and hence securing the access to sensitive data.
    • We use to run different type of analytics services to get the better result which is hectic if done manually or with human efforts.
    • We also use to collect bulk of data with the help of this tool and run customized test cases for better efficiency of result and better decision making. The result are very crucial and helps in taking big decision.
    • It supports different or we can say heterogeneous database vendors like the Oracle, SQL, and hence make the task easy.
    Incentivized
    Read full review
    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
    Cons
    Microsoft
    • There is very least content available on Microsoft docs and the Internet to get through with AAS.
    • i faced lots of connection issues while implementation.
    • The need for serious platform experience or expertise.
    Incentivized
    Read full review
    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
    Likelihood to Renew
    Microsoft
    No answers on this topic
    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
    Usability
    Microsoft
    No answers on this topic
    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
    Reliability and Availability
    Microsoft
    No answers on this topic
    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
    Performance
    Microsoft
    No answers on this topic
    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
    Support Rating
    Microsoft
    No answers on this topic
    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
    Alternatives Considered
    Microsoft
    The platform has vast number of features and modules. The UI is sleek and once you get to use to it, you will be able to do a lot of stuff. Also support for data sources is more in Azure Analysis Services.
    Incentivized
    Read full review
    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
    Contract Terms and Pricing Model
    Microsoft
    No answers on this topic
    Google
    None so far. Very satisfied with the transparency on contract terms and pricing model.
    Read full review
    Scalability
    Microsoft
    No answers on this topic
    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
    Professional Services
    Microsoft
    No answers on this topic
    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
    Return on Investment
    Microsoft
    • The tool has helped us a lot for taking critical decision which has resulted in the increase of profit of organization by 18 percent.
    • Return on investment is 70 percent as we are unable to utilize the tool with full functionalities, so we are still testing some of the use cases.
    • Human effort has been reduced and task has become automated hence helped in cost management
    Incentivized
    Read full review
    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
    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.