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Databases · head to head

BigQuery vs Google Cloud Platform

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
Google Cloud Platform logo

Google Cloud Platform

Cloud

Trusted by millions of enterprises

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.; Google Cloud Platform the $300 Free Trial credit expires 90 days from signup, whichever comes first with spending it
  • They diverge on capability: BigQuery covers Serverless compute, Google Cloud Platform covers Compute Engine.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Google Cloud Platform actually diverge.

Attributes where BigQuery and Google Cloud Platform differ
AttributeBigQueryGoogle Cloud Platform
PlatformsWeb, Cloud APIWeb, Api, Cli
CategoryDatabasesCloud

Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), user rating (Not yet rated), founded (2008).

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 Google Cloud Platform

  • Compute Engine
  • App Engine
  • Cloud Run
  • Cloud Storage
  • Cloud SQL
  • BigQuery
  • Dataflow
  • Cloud Pub/Sub

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 Google Cloud Platform
  • Bursty analytical workloads with long idle periods, where paying per query beats keeping a cluster runningnot Google Cloud Platform
  • Event and clickstream analytics ingested continuously through the Storage Write API and queried without a load windownot Google Cloud Platform
  • Analytics teams with no infrastructure staff, where the absence of anything to tune or patch is worth more than dialect portabilitynot Google Cloud Platform

Google Cloud Platform

  • Cloud infrastructure and computing servicesnot BigQuery
  • Machine learning and data analyticsnot 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.

Google Cloud Platform

  • The $300 Free Trial credit expires 90 days from signup, whichever comes first with spending it
  • Free Tier Compute Engine is limited to one non-preemptible e2-micro instance per month and only in the us-west1, us-central1 or us-east1 regions
  • Free Tier Compute Engine includes only 30 GB-months of standard persistent disk and 1 GB of outbound North America data transfer per month
  • Free Tier Cloud Storage covers 5 GB-months of regional storage in US regions only, 5,000 Class A and 50,000 Class B operations per month
  • Free Tier outbound data transfer allowances exclude destinations in China and Australia
  • Compute Engine resources are governed by allocation quotas that require a quota increase request to exceed

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

Google Cloud Platform

Free
  • Free TierFree
    • Compute Engine 744 hours/month
    • Cloud Storage 5GB
    • Cloud SQL 250MB storage

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 Google Cloud Platform if

  • You need compute engine.
  • You want to start without paying.
  • You work on Web, Api, Cli.
  • You also want app engine.
Google Cloud Platform review

Questions people ask

Is BigQuery or Google Cloud Platform better?
Neither clearly leads. BigQuery starts at Free and Google Cloud Platform at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Google Cloud Platform?
BigQuery starts at Free and Google Cloud Platform at Free.
Does BigQuery or Google Cloud Platform run on more platforms?
BigQuery runs on Web, Cloud API. Google Cloud Platform runs on Web, Api, Cli.
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 Google Cloud Platform is typically brought in for.
What can BigQuery do that Google Cloud Platform cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Google Cloud Platform covers Compute Engine, App Engine, Cloud Run, Cloud 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.

Google Cloud Platform: What is Google Cloud Platform's pricing model?

Google Cloud uses usage-based pay-as-you-go pricing with options for committed use discounts at 1-year or 3-year terms, which can reduce costs by 25-70%. Pricing varies by region, service, and usage volume.

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.

Google Cloud Platform: Does Google Cloud offer a free tier?

Yes, Google Cloud offers an always-free tier with generous free allowances for development, plus $300 in free credits for new customers during their first 90 days.

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.

Google Cloud Platform: How do committed use discounts work?

Users can commit to 1-year or 3-year usage of specific services to receive discounts of 25-70% compared to on-demand pricing. These discounts apply to compute, storage, and other services.

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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