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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)

    TeamDesk

    Score9 out of 10
    N/ATeamDesk is a low-code development platform for online database creation. Business owners or managers can build a unique web database solution without any programming to facilitate working with data, organize routine work and create an accessible data source for teams.

    $49

    5 users included

    Pricing
    Google BigQueryTeamDesk
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Starter Edition
    $49
    5 users included
    Team Edition
    $99
    10 users included
    Enterprise Edition
    $249
    10 users included, Unlimited databases, Sub-domain
    Offerings
    Pricing Offerings
    Google BigQueryTeamDesk
    Free Trial
    YesYes
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeOptional
    Additional Details——
    More Pricing Information
    Community Pulse
    Google BigQueryTeamDesk
    Considered Both Products
    Google
    No answer on this topic
    ForeSoft Corporation
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    100%
    Would buy again
    12 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    100%
    Delivers good value for the price
    12 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    100%
    Happy with the feature set
    12 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
    11 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    100%
    Implementation went as expected
    12 Answers
    Features
    Google BigQueryTeamDesk
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and TeamDesk
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    TeamDesk
    -
    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
    Low-Code Development
    Comparison of Low-Code Development features of Google BigQuery and TeamDesk
    Feature
    Google BigQuery
    -
    Ratings
    TeamDesk
    9.2
    12 Ratings
    9% above category average
    Visual Modeling00 Ratings8.01 Ratings
    Platform Security00 Ratings10.01 Ratings
    Platform User Management00 Ratings8.712 Ratings
    Reusability00 Ratings10.01 Ratings
    Platform Scalability00 Ratings9.110 Ratings
    Best Alternatives
    Google BigQueryTeamDesk
    Small Businesses
    MongoDB Atlas
    Score7.8 out of 10
    Zoho Creator
    Score7.7 out of 10
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    AppSheet
    Score8.2 out of 10
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    Oracle APEX
    Score9.1 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryTeamDesk
    Likelihood to Recommend
    9.0
    (79 ratings)
    9.0
    (12 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    -
    (0 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)
    9.1
    (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 BigQueryTeamDesk
    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
    ForeSoft Corporation
    Teamdesk is perfect for any operational tracking requirements for companies small or large, and any situation where you need to integrate with other systems since it can be set up to do that flexibly via its API and Webhooks. For example, you could track contacts, time and expense, projects and tasks, schedules, web leads, check-ins, order entry, quotes and invoices, support ticketing, and use the more advanced features to integrate with other systems to pull in currency exchange rates, various lists of data from other databases, send faxes, send bulk emails and so on. It does not do offline storage, so it would not be appropriate for a situation that offline work.
    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
    ForeSoft Corporation
    • Provide a very good, customizable user management system.
    • Gives a lot of flexibility to customize database to your needs without requiring coding skills. Even allows to customize interface if you can code in html.
    • Provides unlimited space and records.
    • Gives an opportunity to have a database on EU servers to comply with GDPR
    • Offers very good pricing options comparing to competitors (Salesforce, Quickbase, etc.) and offers unlimited space.
    • Gives an opportunity to share your ideas how to improve the platform, many of which are being implemented
    • Customers service if very helpful and friendly. All my questions were answered within a couple hours.
    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
    ForeSoft Corporation
    • The only down side that I see, is that you have to be willing to spend some time creating your database. You start with a blank canvas and all the tools you need to design a custom database. But, you have to take the time to do it. If you take that time, it is well worth it.
    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
    ForeSoft Corporation
    No answers on this topic
    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
    ForeSoft Corporation
    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
    ForeSoft Corporation
    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
    ForeSoft Corporation
    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
    ForeSoft Corporation
    They are simply amazing. Very fast, like I have a personal support person standing by for me and always solves my problem in one go.
    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
    ForeSoft Corporation
    Quickbase is a good product which I have been using for 5 years (powerful, nice interface) but - not so powerful as TeamDesk - started to move toward large companies (>50 people) - more expensive than TeamDesk Zoho was not as flexible as TeamDesk Caspio was not as powerful as TeamDesk
    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
    ForeSoft Corporation
    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
    ForeSoft Corporation
    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
    ForeSoft Corporation
    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
    ForeSoft Corporation
    • The per user cost is significantly lower than any prior option we have tried. The time spent getting things set up was time well spent for the overall long-term savings.
    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.

    TeamDesk Screenshots

    Screenshot of Table Dashboard exampleScreenshot of Record Form exampleScreenshot of Tile View example