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Databases · head to head

BigQuery vs Microsoft Azure

BigQuery logo

BigQuery

Databases

Google Cloud's serverless analytical warehouse, billed either by bytes scanned per query or by reserved compute slots.

From
Free
Rated
-
Full reviewWebsite
Microsoft Azure logo

Microsoft Azure

Cloud

Open and flexible cloud services

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: BigQuery on-demand billing charges for bytes read from every column a query references, so an unqualified select or a missing partition filter turns a routine query into a large bill, and the cost is discovered after the fact rather than at review time.; Microsoft Azure the 12 months of free services is available only to new customers who have not previously had an Azure account or received 12 months of free services
  • They diverge on capability: BigQuery covers Serverless compute, Microsoft Azure covers Virtual Machines.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Microsoft Azure actually diverge.

Attributes where BigQuery and Microsoft Azure differ
AttributeBigQueryMicrosoft Azure
PlatformsWeb, Cloud APIWeb, Api, Desktop, Mobile
CategoryDatabasesCloud
Founded20082010

Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in BigQuery

  • Serverless compute
  • Separation of storage and compute
  • Two pricing models
  • Partitioning and clustering
  • Materialised views
  • BigQuery ML
  • Storage Write API
  • BI Engine

Only in Microsoft Azure

  • Virtual Machines
  • App Service
  • SQL Database
  • Blob Storage
  • Azure Cosmos DB
  • Functions
  • Service Fabric
  • API Management

What people use each for

The jobs each tool is most often brought in to do.

BigQuery

  • A warehouse for an organisation already on Google Cloud, where identity, logging and billing are consolidated in the same placenot Microsoft Azure
  • Bursty analytical workloads with long idle periods, where paying per query beats keeping a cluster runningnot Microsoft Azure
  • Event and clickstream analytics ingested continuously through the Storage Write API and queried without a load windownot Microsoft Azure
  • Analytics teams with no infrastructure staff, where the absence of anything to tune or patch is worth more than dialect portabilitynot Microsoft Azure

Microsoft Azure

  • Cloud infrastructure and computingnot BigQuery
  • Database and storage servicesnot BigQuery
  • AI and machine learning servicesnot BigQuery
  • Enterprise application hostingnot BigQuery

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

BigQuery

  • On-demand billing charges for bytes read from every column a query references, so an unqualified select or a missing partition filter turns a routine query into a large bill, and the cost is discovered after the fact rather than at review time.
  • There is no way to join tables that live in different regions, so a data estate split across regions for residency reasons has to be reconciled with copies and the storage and transfer that implies.
  • It is not built for point lookups; retrieving a single row has latency measured in hundreds of milliseconds or more, so BigQuery cannot serve an application's read path and always needs a second store in front of it.
  • Frequent small mutations run into DML concurrency limits and the cost of rewriting storage blocks, so a workload that updates individual rows continuously behaves badly compared with an append-only design.
  • The compute exists only inside Google Cloud, so while tables can be exported, the accumulated GoogleSQL, scheduled queries, authorised views, ML models and IAM structure do not move, and switching warehouses is a rewrite of the analytical layer.

Microsoft Azure

  • The 12 months of free services is available only to new customers who have not previously had an Azure account or received 12 months of free services
  • The 12 months free offer is not available to customers who sign up directly for pay as you go in China and India
  • Customers who try Azure free must move to pay as you go within 30 days to keep receiving the 12 months of free services
  • Free services are capped at specified monthly amounts, and only some of them are always free

Pricing, plan by plan

BigQuery

Free
  • Free TierFree
    • 1TB queries/month
    • 10GB storage/month
    • Standard support
  • On-demand$6.25/TB
    • Pay per query
    • Pay per storage
    • All features

Microsoft Azure

Free
  • Free AccountFree
    • $200 credit for 30 days
    • Popular services 12 months free
    • 40+ services always free

Which should you pick?

Choose BigQuery if

  • You need serverless compute.
  • You want to start without paying.
  • You work on Web, Cloud API.
  • You also want separation of storage and compute.
BigQuery review

Choose Microsoft Azure if

  • You need virtual machines.
  • You want to start without paying.
  • You work on Web, Api, Desktop, Mobile.
  • You also want app service.
Microsoft Azure review

Questions people ask

Is BigQuery or Microsoft Azure better?
Neither clearly leads. BigQuery starts at Free and Microsoft Azure at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Microsoft Azure?
BigQuery starts at Free and Microsoft Azure at Free.
Does BigQuery or Microsoft Azure run on more platforms?
BigQuery runs on Web, Cloud API. Microsoft Azure runs on Web, Api, Desktop, Mobile.
Can I use BigQuery for free?
Both have a free tier, so you can try either at no cost before committing.
What is BigQuery best used for?
BigQuery is most often used for a warehouse for an organisation already on google cloud, where identity, logging and billing are consolidated in the same place, bursty analytical workloads with long idle periods, where paying per query beats keeping a cluster running, event and clickstream analytics ingested continuously through the storage write api and queried without a load window, analytics teams with no infrastructure staff, where the absence of anything to tune or patch is worth more than dialect portability. Of those, a warehouse for an organisation already on google cloud, where identity, logging and billing are consolidated in the same place and bursty analytical workloads with long idle periods, where paying per query beats keeping a cluster running are not what Microsoft Azure is typically brought in for.
What can BigQuery do that Microsoft Azure cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Microsoft Azure covers Virtual Machines, App Service, SQL Database, Blob Storage.

Answered from the vendors’ own pages

BigQuery: How is BigQuery actually billed?

Storage is billed separately from compute. Compute is either on-demand, priced by the bytes a query reads from the referenced columns, or capacity-based, where you reserve autoscaling slots. Most cost surprises come from on-demand queries that scan more than expected.

Microsoft Azure: How much does Microsoft Azure cost?

Azure uses consumption-based pricing where you pay only for resources used and scale as you grow, with no fixed monthly fee. Prices are listed in USD globally, and pricing varies by service, region, and usage patterns.

Source
BigQuery: How do I control query cost?

Partition and cluster tables so queries prune data, select only the columns needed, use materialised views for repeated aggregations, and set maximum bytes billed on queries so a runaway scan fails instead of billing.

Microsoft Azure: How can I save money on Azure services?

Azure offers savings up to 65% on select compute services through Azure Savings Plans with one- or three-year commitments. Using Azure Hybrid Benefit with existing Windows Server and SQL Server licenses plus reservations can save up to 85% compared to standard rates.

Source
BigQuery: Can I use it without being on Google Cloud?

The service only runs on Google Cloud. BigQuery Omni can query data held in S3 or Azure storage, but the compute is still Google's and the account relationship is still with Google.

Microsoft Azure: Does Azure offer a free tier?

Azure provides free tier services for new users and perpetually free options, including free Spot Virtual Machines, dev/test pricing for development workloads, and access to the Azure Pricing Calculator to estimate monthly costs before deployment.

Source
BigQuery: Is it suitable for serving application queries?

No. Latency for single-row reads is far too high. BigQuery is an analytical warehouse and application read paths need a transactional database or a cache in front of it.

BigQuery: When should I move from on-demand to capacity pricing?

When on-demand spend becomes both large and predictable, or when unpredictable spend is a bigger problem than query queueing. The switch trades a variable bill for a fixed one plus contention between workloads.

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