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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)

    Tableau Server

    Score7.5 out of 10
    N/ATableau Server allows Tableau Desktop users to publish dashboards to a central server to be shared across their organizations. The product is designed to facilitate collaboration across the organization. It can be deployed on a server in the data center, or it can be deployed on a public cloud.

    $12

    Per User Per Month

    Pricing
    Google BigQueryTableau Server
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Viewer
    $12.00
    Per User Per Month
    Explorer
    $35.00
    Per User Per Month
    Creator
    $70.00
    Per User Per Month
    Offerings
    Pricing Offerings
    Google BigQueryTableau Server
    Free Trial
    YesYes
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Google BigQueryTableau Server
    Considered Both Products
    Google
    Chose Google BigQuery
    It's easier to connect data between BigQuery and Looker Studio instead of connecting the data between BigQuery and Tableau in terms of data explore or dashboard creating. Therefore we are considering migrating dashboards from Tableau to Looker Studio for the whole company.
    On …
    Incentivized
    Chose Google BigQuery
    I personally find it by far simpler than Amazon Redshift due it's onboarding seamlessness. For a quick start and simplify tye access to read the data big query provide better user experience and a smoother user interface. More importantly, the fact that Big Query can be easily …
    Incentivized
    Chose Google BigQuery
    Other locally hosted solutions are capable of providing the required level of performance, but the administration requirements are significantly more involved than with BigQuery. Additionally, there are capacity and availability concerns with locally hosted platforms that are a …
    Incentivized
    Tableau
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    75%
    Would buy again
    6 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    75%
    Delivers good value for the price
    6 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    88%
    Happy with the feature set
    7 Answers
    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
    71%
    Implementation went as expected
    5 Answers
    Features
    Google BigQueryTableau Server
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Tableau Server
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Tableau Server
    -
    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 Tableau Server
    Feature
    Google BigQuery
    -
    Ratings
    Tableau Server
    8.4
    95 Ratings
    3% above category average
    Pixel Perfect reports00 Ratings9.129 Ratings
    Customizable dashboards00 Ratings7.094 Ratings
    Report Formatting Templates00 Ratings9.081 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of Google BigQuery and Tableau Server
    Feature
    Google BigQuery
    -
    Ratings
    Tableau Server
    7.8
    95 Ratings
    3% below category average
    Drill-down analysis00 Ratings8.095 Ratings
    Formatting capabilities00 Ratings8.093 Ratings
    Integration with R or other statistical packages00 Ratings8.059 Ratings
    Report sharing and collaboration00 Ratings7.089 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of Google BigQuery and Tableau Server
    Feature
    Google BigQuery
    -
    Ratings
    Tableau Server
    7.2
    91 Ratings
    13% below category average
    Publish to Web00 Ratings8.085 Ratings
    Publish to PDF00 Ratings7.084 Ratings
    Report Versioning00 Ratings8.070 Ratings
    Report Delivery Scheduling00 Ratings8.077 Ratings
    Delivery to Remote Servers00 Ratings5.19 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of Google BigQuery and Tableau Server
    Feature
    Google BigQuery
    -
    Ratings
    Tableau Server
    8.3
    90 Ratings
    4% above category average
    Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.086 Ratings
    Location Analytics / Geographic Visualization00 Ratings8.085 Ratings
    Predictive Analytics00 Ratings8.064 Ratings
    Pattern Recognition and Data Mining00 Ratings8.01 Ratings
    Access Control and Security
    Comparison of Access Control and Security features of Google BigQuery and Tableau Server
    Feature
    Google BigQuery
    -
    Ratings
    Tableau Server
    10.0
    95 Ratings
    16% above category average
    Multi-User Support (named login)00 Ratings10.093 Ratings
    Role-Based Security Model00 Ratings10.090 Ratings
    Multiple Access Permission Levels (Create, Read, Delete)00 Ratings10.092 Ratings
    Report-Level Access Control00 Ratings10.01 Ratings
    Single Sign-On (SSO)00 Ratings10.062 Ratings
    Mobile Capabilities
    Comparison of Mobile Capabilities features of Google BigQuery and Tableau Server
    Feature
    Google BigQuery
    -
    Ratings
    Tableau Server
    8.1
    79 Ratings
    4% above category average
    Responsive Design for Web Access00 Ratings10.077 Ratings
    Mobile Application00 Ratings7.061 Ratings
    Dashboard / Report / Visualization Interactivity on Mobile00 Ratings7.068 Ratings
    Application Program Interfaces (APIs) / Embedding
    Comparison of Application Program Interfaces (APIs) / Embedding features of Google BigQuery and Tableau Server
    Feature
    Google BigQuery
    -
    Ratings
    Tableau Server
    6.4
    46 Ratings
    19% below category average
    REST API00 Ratings8.040 Ratings
    Javascript API00 Ratings8.037 Ratings
    iFrames00 Ratings6.040 Ratings
    Java API00 Ratings5.57 Ratings
    Themeable User Interface (UI)00 Ratings6.19 Ratings
    Customizable Platform (Open Source)00 Ratings4.67 Ratings
    Best Alternatives
    Google BigQueryTableau Server
    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 BigQueryTableau Server
    Likelihood to Recommend
    9.0
    (79 ratings)
    8.0
    (111 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    10.0
    (20 ratings)
    Usability
    6.6
    (6 ratings)
    8.0
    (17 ratings)
    Availability
    7.3
    (1 ratings)
    9.0
    (9 ratings)
    Performance
    6.4
    (1 ratings)
    8.1
    (8 ratings)
    Support Rating
    4.8
    (11 ratings)
    3.0
    (18 ratings)
    In-Person Training
    -
    (0 ratings)
    8.0
    (4 ratings)
    Online Training
    -
    (0 ratings)
    9.0
    (9 ratings)
    Implementation Rating
    -
    (0 ratings)
    9.1
    (13 ratings)
    Configurability
    6.4
    (1 ratings)
    8.0
    (1 ratings)
    Contract Terms and Pricing Model
    10.0
    (1 ratings)
    -
    (0 ratings)
    Data Sharing and Collaboration
    -
    (0 ratings)
    5.1
    (79 ratings)
    Data Sources
    -
    (0 ratings)
    6.6
    (82 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 BigQueryTableau Server
    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
    Tableau
    Whole funnel and specific channel performance from upper to lower funnel metrics. The ability to view full channel performance for some time, such as weekly, monthly, or quarterly, has truly been monumental in how my team optimizes specific channels and campaigns. Daily performance tracking is a bit overwhelming, with load times and having to refresh specific live views over time. It can be challenging to do so at times, as extensive dashboards take much longer to load.
    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
    Tableau
    • It's good at doing what it is designed for: accessing visualizations without having to download and open a workbook in Tableau Desktop. The latter would be a very inefficient method for sharing our metrics, so I am glad that we have Tableau Server to serve this function.
    • Publishing to Tableau Server is quick and easy. Just a few clicks from Tableau Desktop and a few seconds of publishing through an average speed network, and the new visualizations are live!
    • Seeing details on who has viewed the visualization and when. This is something particularly useful to me for trying to drive adoption of some new pages, so I really appreciate the granularity provided in Tableau Server
    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
    Tableau
    • Tableau Server has had some issue handling some of our larger data sets. Our extract refreshes fail intermittently with no obvious error that we can fix
    • Tableau Server has been hard to work with before they launched their new Rest API, which is also a little tricky to work with
    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
    Tableau
    It simply is used all the time by more and more people. Migrating to something else would involve lots of work and lots of training. The renewal fee being fair, it simply isn't worth migrating to a different tool for now.
    Incentivized
    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
    Tableau
    Tableau Server takes training and experience in order to unlock the application's full potential. This is best handled by a qualified data scientist or data analytics manager. Tableau user interface layout, nomenclature, and command structure take time and training to become proficient with. Integration and connectivity require proper IT developer support.
    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
    Tableau
    Our instance of Tableau Server was hosted on premises (I believe all instances are) so if there were any outages it was normally due to scheduled maintenance on our end. If the Tableau server ever went down, a quick restart solved most issues
    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
    Tableau
    While there are definitely cases where a user can do things that will make a particular worksheet or dashboard run slowly, overall the performance is extremely fast. The user experience of exploratory analysis particularly shines, there's nothing out there with the polish of Tableau.
    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
    Read full review
    Tableau
    We have consistently had highly satisfactory results every time we've reached out for help. Our contractor, used for Tableau server maintenance and dashboard development is very technically skilled. When he hits a roadblock on how to do something with Tableau, the support staff have provided timely and useful guidance. He frequently compares it to Cognos and says that while Cognos has capabilities Tableau doesn't, the bottom line value for us is a no-brainer
    Incentivized
    Read full review
    In-Person Training
    Google
    No answers on this topic
    Tableau
    In our case, they hired a private third party consultant to train our dept. It was extremely boring and felt like it dragged on. Everything I learned was self taught so I was not really paying attention. But I do think that you can easily spend a week on the tool and go over every nook and cranny. We only had the consultant in for a day or two.
    Read full review
    Online Training
    Google
    No answers on this topic
    Tableau
    The Tableau website is full of videos that you can follow at your own pace. As a very small company with a Tableau install, access to these free resources was incredibly useful to allowing me to implement Tableau to its potential in a reasonable and proportionate manner.
    Read full review
    Implementation Rating
    Google
    No answers on this topic
    Tableau
    Implementation was over the phone with the vendor, and did not go particularly well. Again, think this was our fault as our integration and IT oversight was poor, and we made errors. Would they have happened had a vendor been onsite? Not sure, probably not, but we probably wouldn't have paid for that either
    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
    Tableau
    Today, if my shop is largely Microsoft-centric, I would be hard pressed to choose a product other than Power BI. Tableau was the visualization leader for years, but Microsoft has caught up with them in many areas, and surpassed them in some. Its ability to source, transform, and model data is superior to Tableau. Tableau still has the lead in some visualizations, but Power BI's rise is evidenced by its ever-increasing position in the leadership section of the Gartner Magic Quadrant.
    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
    Tableau
    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
    Tableau
    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
    Tableau
    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
    Tableau
    • Tableau does take dedicated FTE to create and analyze the data. It's too complex (and powerful) a product not to have someone dedicated to developing with it.
    • There are some significant setup for the server product.
    • Once sever setup is complete, it's largely "fire and forget" until an update is necessary. The server update process is cumbersome.
    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.

    Tableau Server Screenshots

    Screenshot of Tableau Server interface and administration view 1.Screenshot of Tableau Server interface and administration view 2.Screenshot of Tableau Server permissions view.Screenshot of Tableau Services Manager (TSM) view 1.Screenshot of Tableau Services Manager (TSM) view 2.