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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)

    Vultr

    Score8.7 out of 10
    N/AVultr is an independent cloud computing platform on a mission to provide businesses and developers around the world with unrivaled ease of use, price-to-performance, and global reach.

    $2.50

    per month

    Pricing
    Google BigQueryVultr
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Block Storage
    $1
    per month
    Cloud Compute
    $2.50
    per month
    Object Storage
    $5
    per month
    Kubernetes Engine
    $10
    per month
    Load Balancers
    $10
    per month
    Managed Databases
    $15
    per month
    Optimized Cloud Compute
    $28
    per month
    Cloud GPU
    $90
    per month
    Bare Metal
    $120
    per month
    Offerings
    Pricing Offerings
    Google BigQueryVultr
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional DetailsPricing is based on specifications chosen in each product category. Bandwidth is also included up to a certain amount per month.
    More Pricing Information
    Features
    Google BigQueryVultr
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Vultr
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Vultr
    -
    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
    Infrastructure-as-a-Service (IaaS)
    Comparison of Infrastructure-as-a-Service (IaaS) features of Google BigQuery and Vultr
    Feature
    Google BigQuery
    -
    Ratings
    Vultr
    8.8
    62 Ratings
    6% above category average
    Service-level Agreement (SLA) uptime00 Ratings9.555 Ratings
    Dynamic scaling00 Ratings9.047 Ratings
    Elastic load balancing00 Ratings9.334 Ratings
    Pre-configured templates00 Ratings9.143 Ratings
    Monitoring tools00 Ratings6.748 Ratings
    Pre-defined machine images00 Ratings8.953 Ratings
    Operating system support00 Ratings9.358 Ratings
    Security controls00 Ratings8.651 Ratings
    Automation00 Ratings8.741 Ratings
    Best Alternatives
    Google BigQueryVultr
    Small Businesses
    MongoDB Atlas
    Score7.8 out of 10
    IBM Cloud Object Storage
    Score9 out of 10
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    IBM Cloud Bare Metal Servers
    Score8.7 out of 10
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    SAP on IBM Cloud
    Score9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryVultr
    Likelihood to Recommend
    9.0
    (79 ratings)
    8.9
    (65 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    7.2
    (6 ratings)
    Usability
    6.6
    (6 ratings)
    7.9
    (6 ratings)
    Availability
    7.3
    (1 ratings)
    9.7
    (2 ratings)
    Performance
    6.4
    (1 ratings)
    9.7
    (2 ratings)
    Support Rating
    4.8
    (11 ratings)
    8.2
    (5 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.9
    (3 ratings)
    Configurability
    6.4
    (1 ratings)
    9.7
    (2 ratings)
    Contract Terms and Pricing Model
    10.0
    (1 ratings)
    6.2
    (2 ratings)
    Ease of integration
    7.3
    (1 ratings)
    10.0
    (1 ratings)
    Product Scalability
    7.3
    (1 ratings)
    9.7
    (2 ratings)
    Professional Services
    8.2
    (2 ratings)
    10.0
    (1 ratings)
    Vendor post-sale
    -
    (0 ratings)
    9.7
    (2 ratings)
    Vendor pre-sale
    -
    (0 ratings)
    9.7
    (2 ratings)
    User Testimonials
    Google BigQueryVultr
    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
    Vultr
    Vultr is amazing for anyone who needs a server and wants to spend time taking care of it, or for someone who wants in on it. WordPress Minecraft kids can use Votr. The scenario is not as appropriate for the people who do not have as much technical knowledge and capacity and don't want to invest in it, not because of Votr itself, but because VPS is not kids' play. Even though we have a Minecraft server and they're quite easy, there will come a time when, if you put your business infrastructure inside Vultr or any VPS, you need to take care of it. Otherwise, it will have a problem.
    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
    Vultr
    • Email hosting is viable because they maintain a clean IP reputation.
    • They have an easy to use platform with console access.
    • They offer many useful OS choices to fit any project.
    • The price is fair and affordable.
    • They offer VPC for large projects.
    • I have never experienced down time, so the network is stable and well maintained.
    • Responsive and helpful support.
    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
    Vultr
    • There have been times where my VPS is affected by a noisy nieghbour. Would be good to have this actively monitored and mitigated.
    • Being based in South Africa, it would be nice to have pricing parity options for weaker countries (even if for lower level servers). Sometimes I need throw away or temporary servers, but USD 5 is still expensive in weaker currencies, and can stack up quickly.
    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
    Vultr
    Just a great product with no bells and whistles, which is the advantage. We spend very little time learning and using Vultr and more time using the systems we have in Vultr to complete our tasks. Not having to worry about the IT overhead is huge and saves a great deal of time
    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
    Vultr
    easy to use and configure. great bang for the buck. I need an affordable solution to host in the cloud data from systems installed at our client's site with the ability to drill down and change the configuration remotely. Vultr enabled us to do that in an efficient and affordable way.
    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
    Vultr
    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
    Vultr
    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
    Vultr
    Vultr makes it easy to contact technical support. The techs are very competent. In a number of occasions they have bounced the responsibility back to me when they could have saved us all time and heartache by simply implementing the solution directly
    Incentivized
    Read full review
    Implementation Rating
    Google
    No answers on this topic
    Vultr
    Vultr implementation seemed based on open-source tools and basic cloud principles - some things were more complicated to do compared with more developed cloud providers, but on the other hand it was more extensible by open-source tools.
    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
    Vultr
    Linode is a more old-school offering. Linode pricing model and infrastructure rely on classic Virtual Machines. What we like about Vultr is that they offer the same at the front, but in the back, the machines are much more flexible and can be tailor-made to our needs, which of course also impacts the costs of running the infrastructure.
    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
    Vultr
    Pricing is fair and did not increase
    Incentivized
    Read full review
    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
    Vultr
    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
    Vultr
    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
    Vultr
    • We have experienced a 200% return on using Vultr products with a 100% Customer Satisfaction rating.
    • Vultr gives us the regions to deploy where our small business customers are located.
    • Vultr has helped us scale up our company and our cloud solutions.
    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.

    Vultr Screenshots

    Screenshot of Vultr's control panel helps users spend less time managing infrastructure.Screenshot of Vultr's services offer additional configuration and inside of the simplified control panel.Screenshot of a display of when peak activity happens on an application. The server health graphs provide insight from the moment the server is created.Screenshot of Vultr's interface, which allows users to deploy high performance servers worldwide from any device.Screenshot of how to reach the 24/7/365 technical support team that is available through Vultr's ticketing system.