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AWS (Amazon Web Services) vs BigQuery

AWS (Amazon Web Services) logo

AWS (Amazon Web Services)

Cloud

The leading cloud computing platform

From
Free
Rated
-
Full reviewWebsite
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

The short version

  • Each has a real cost: AWS (Amazon Web Services) data transfer in is free and data transfer out is charged, which is the standard source of unexpected bills; 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.
  • They diverge on capability: AWS (Amazon Web Services) covers EC2 - Virtual Servers, BigQuery covers Serverless compute.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which AWS (Amazon Web Services) and BigQuery actually diverge.

Attributes where AWS (Amazon Web Services) and BigQuery differ
AttributeAWS (Amazon Web Services)BigQuery
PlatformsWeb, Api, Cli, MobileWeb, Cloud API
CategoryCloudDatabases
Founded20062008

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 AWS (Amazon Web Services)

  • EC2 - Virtual Servers
  • S3 - Object Storage
  • RDS - Managed Database
  • Lambda - Serverless Computing
  • CloudFront - CDN
  • VPC - Virtual Network
  • IAM - Access Management
  • CloudWatch - Monitoring

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

What people use each for

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

AWS (Amazon Web Services)

  • Web hostingnot BigQuery
  • Data storagenot BigQuery
  • Machine learningnot BigQuery
  • Big data analyticsnot BigQuery
  • Application developmentnot BigQuery

BigQuery

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

Where each one falls short

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

AWS (Amazon Web Services)

  • Data transfer in is free and data transfer out is charged, which is the standard source of unexpected bills
  • Discounts require one or three year Savings Plan commitments rather than being automatic
  • Every service is priced separately, so a working architecture has no single published cost
  • The free tier is a promotional allowance rather than an ongoing free plan

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.

Pricing, plan by plan

AWS (Amazon Web Services)

Free
  • AWS Free TierFree
    • EC2 750 hours/month
    • 5GB S3 storage
    • 20GB data transfer
  • Pay-As-You-GoFree
    • No upfront payment
    • No long-term commitments
    • Pay only for what you use

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

Which should you pick?

Choose AWS (Amazon Web Services) if

  • You need ec2 - virtual servers.
  • You want to start without paying.
  • You work on Web, Api, Cli, Mobile.
  • You also want s3 - object storage.
AWS (Amazon Web Services) review

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

Questions people ask

Is AWS (Amazon Web Services) or BigQuery better?
Neither clearly leads. AWS (Amazon Web Services) starts at Free and BigQuery at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS (Amazon Web Services) or BigQuery?
AWS (Amazon Web Services) starts at Free and BigQuery at Free.
Does AWS (Amazon Web Services) or BigQuery run on more platforms?
AWS (Amazon Web Services) runs on Web, Api, Cli, Mobile. BigQuery runs on Web, Cloud API.
Can I use AWS (Amazon Web Services) for free?
Both have a free tier, so you can try either at no cost before committing.
What is AWS (Amazon Web Services) best used for?
AWS (Amazon Web Services) is most often used for web hosting, data storage, machine learning, big data analytics. Of those, web hosting and data storage are not what BigQuery is typically brought in for.
What can AWS (Amazon Web Services) do that BigQuery cannot?
AWS (Amazon Web Services) covers EC2 - Virtual Servers, S3 - Object Storage, RDS - Managed Database, Lambda - Serverless Computing. BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering.

Answered from the vendors’ own pages

AWS (Amazon Web Services): What are AWS's payment options and pricing models?

AWS offers four pricing approaches: pay-as-you-go (you pay only for what you use), flat-rate plans combining multiple services into one monthly price without overages, Savings Plans offering discounts on compute and machine learning with 1- or 3-year commitments, and volume-based tiered pricing where costs decrease as usage increases.

Source
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.

AWS (Amazon Web Services): Are there contracts, termination fees, or commitments required for AWS?

No long-term contracts are required for AWS services. No termination fees apply once you stop using the service. Savings Plans provide optional 1- or 3-year commitments with discounted hourly rates, but you can revert to pay-as-you-go pricing anytime.

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.

AWS (Amazon Web Services): Does AWS offer a free tier?

AWS provides a free tier that offers hands-on experience with AWS products at no charge. The free tier allows new customers to try eligible services before committing to paid usage.

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.

AWS (Amazon Web Services): How do I estimate my AWS costs?

AWS provides the AWS Pricing Calculator and Cost Explorer tool to estimate costs for single or multiple services. AWS also offers cost optimization recommendations, performance reporting, and budget alerts to help track and control spending.

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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