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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)

    Visual Studio

    Score8.8 out of 10
    N/AVisual Studio (now in the 2022 edition) is a 64-bit IDE that makes it easier to work with bigger projects and complex workloads, boasting a fluid and responsive experience for users. The IDE features IntelliCode, its automatic code completion tools that understand code context and that can complete up to a whole line at once to drive accurate and confident coding.

    $45

    per month

    Pricing
    Google BigQueryVisual Studio
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Professional
    $45.00
    per month
    Enterprise
    $250.00
    per month
    Offerings
    Pricing Offerings
    Google BigQueryVisual Studio
    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 BigQueryVisual Studio
    Considered Both Products
    Google
    Chose Google BigQuery
    In my opinion, Google BigQuery is custom made to be the best data lake system that is easy to use, scalas to fit any business size, has inbuilt security, as well as tools for data integrity. Although a few other tools have some of the same functionality, Google BigQuery is the …
    Incentivized
    Chose Google BigQuery
    Its same as compared to Big query. We go with big query because of clients requirements in project.
    Incentivized
    Microsoft
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    98%
    Would buy again
    40 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    100%
    Delivers good value for the price
    40 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    100%
    Happy with the feature set
    41 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
    32 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    100%
    Implementation went as expected
    36 Answers
    Features
    Google BigQueryVisual Studio
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Microsoft Visual Studio
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Microsoft Visual Studio
    -
    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
    Best Alternatives
    Google BigQueryVisual Studio
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    MongoDB Atlas
    Score7.8 out of 10
    IntelliJ IDEA
    Score9.2 out of 10
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    PyCharm
    Score9.3 out of 10
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    WebStorm
    Score9.6 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryVisual Studio
    Likelihood to Recommend
    9.0
    (79 ratings)
    9.1
    (118 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    10.0
    (3 ratings)
    Usability
    6.6
    (6 ratings)
    9.2
    (15 ratings)
    Availability
    7.3
    (1 ratings)
    -
    (0 ratings)
    Performance
    6.4
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    4.8
    (11 ratings)
    8.8
    (15 ratings)
    In-Person Training
    -
    (0 ratings)
    8.0
    (1 ratings)
    Online Training
    -
    (0 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 BigQueryVisual Studio
    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
    When working with base C# code for desktop and web projects, then Microsoft Visual Studio is ideal as it provides the libraries and interfaces needed to quickly create, test and deploy solutions. It is when slightly more complex scenarios are required that issues can arise. The built-in integration for things like PowerBI Paginated Reports and dashboards is far from ideal.
    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
    • I like how the tabs and panels are organized; everything is gathered together so you can find what you're looking for quickly.
    • If you can't find something, there's a thorough search engine that searches all of Visual Studio's features.
    • The Team Foundation Server feature is fantastic since it allows us to easily deploy and roll back changes on the server.
    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
    • Would be great if there was a better way to save and restore open tabs.
    • The built-in test runner can be improved, for example, by adding the ability to save a set of commonly run tests, etc.
    • Better integration for Microsoft SQL server would be great.
    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
    Microsoft
    VS is the best and is required for building Microsoft applications. The quality and usefulness of the product far out-weight the licensing costs associated with it.
    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
    Microsoft
    I love the overall usability of Microsoft Visual Studio. I’ve been using this IDE for more than 20 years, and I’ve seen it evolve by leaps and bounds. Today, with AI and code-suggestion/completion features, developers no longer need to remember countless libraries, methods, or language syntax, or invest a huge amount of programming effort to complete a project. It truly offers everything a developer needs to program, debug, test, and deploy in a single IDE.
    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
    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
    Microsoft
    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
    Microsoft
    There are many resources available supporting Visual Studio IDE. Microsoft whitepapers, forum posts, and online Visual Studio documentation. There are countless demonstration videos available, as well. If users are having issues, they can call Microsoft Support, but depending on the company's agreement with Microsoft, the number of included support calls will vary from organization to organization. I've found that Microsoft support calls can be hit or miss depending on who you get, but they can usually get you with the right support person for your issue.
    Incentivized
    Read full review
    In-Person Training
    Google
    No answers on this topic
    Microsoft
    IT is very complicated to understand all the functions that the environment has if you are not familiar with this type of development environments. It is important to select a good in-person training to achieve to understand all the possibilities and the capacity of the application. In this case, you will be able to develop a lot type of different applications.
    Incentivized
    Read full review
    Online Training
    Google
    No answers on this topic
    Microsoft
    If you are not accustomed to develop in this type of development environments it would be complicated to follow all the parts of the course because if the course does not include a great tour with all the concepts to develop you will not have the option to understand all the functions.
    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
    Microsoft
    I personally feel Visual Studio IDE has [a] better interface and [is more] user friendly than other IDEs. It has better code maintainability and intellisense. Its inbuilt team foundation server help coders to check on their code then and go. Better nugget package management, quality testing and gives features to extract TRX file as result of testing which includes all the summary of each test case.
    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
    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
    Read full review
    Microsoft
    • Using the integration between Visual Studio and our source control service, the cost of re-work and losing code is drastically reduced.
    • Paid versions of Visual Studio enable developers to be so much more productive than hacked-together open source solutions that it's hard to imagine developing in Windows without it.
    • When combined with support subscriptions and the vast array of free online help options available, Visual Studio saves our developers time by keeping them coding and testing, not wasting their time trying to guess their way out of problems or spend endless hours online hoping to find answers.
    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.