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Databases · head to head

BigQuery vs CosmosDB

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
CosmosDB logo

CosmosDB

Databases

Globally distributed, multi-model database service from Azure

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.; CosmosDB autoscale provisioned throughput enforces a minimum of 1,000 RU/s, billed hourly whether or not the database is used
  • They diverge on capability: BigQuery covers Serverless compute, CosmosDB covers Global Distribution.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and CosmosDB actually diverge.

Attributes where BigQuery and CosmosDB differ
AttributeBigQueryCosmosDB
PlatformsWeb, Cloud APIWeb, Azure
Founded20081975

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

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 CosmosDB

  • Global Distribution
  • Multi-model APIs
  • Elastic Scaling
  • Five Consistency Levels
  • SLA-backed Latency
  • Automatic Indexing
  • Serverless
  • Azure Functions

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

CosmosDB

  • Running a globally distributed multi model database on Azurenot BigQuery
  • Serving low latency reads and writes from multiple Azure regionsnot BigQuery
  • Storing document, key value and graph data behind a managed servicenot 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.

CosmosDB

  • Autoscale provisioned throughput enforces a minimum of 1,000 RU/s, billed hourly whether or not the database is used
  • Provisioned throughput is charged in every region the account is replicated to, so multi region accounts multiply the RU bill
  • Storage charges cover data, indexes and backups in each replicated region
  • Egress out of Azure and between regions is charged, though ingress is free
  • The free allowance is one account per Azure subscription, limited to 1,000 RU/s and 25 GB
  • RU/s rates vary by region and are only shown through the pricing calculator rather than a flat published rate

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

CosmosDB

Free
  • Free TierFree
    • 1000 RU/s
    • 25GB storage
    • First 12 months
  • ServerlessFree
    • Pay per request
    • Auto-scaling
    • Event-driven workloads

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 CosmosDB if

  • You need global distribution.
  • You want to start without paying.
  • You work on Web, Azure.
  • You also want multi-model apis.
CosmosDB review

Questions people ask

Is BigQuery or CosmosDB better?
Neither clearly leads. BigQuery starts at Free and CosmosDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or CosmosDB?
BigQuery starts at Free and CosmosDB at Free.
Does BigQuery or CosmosDB run on more platforms?
BigQuery runs on Web, Cloud API. CosmosDB runs on Web, Azure.
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 CosmosDB is typically brought in for.
What can BigQuery do that CosmosDB cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. CosmosDB covers Global Distribution, Multi-model APIs, Elastic Scaling, Five Consistency Levels.

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.

CosmosDB: Is there a free tier for Azure Cosmos DB?

Yes, Cosmos DB offers a free tier with 1,000 RU/s of throughput and 25 GB of storage per month for the lifetime of the account, available to new accounts.

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.

CosmosDB: How is Cosmos DB priced after the free tier?

Cosmos DB uses three billing models: provisioned throughput billed per request unit per second, vCore pricing for certain APIs, or serverless consumption pricing where you pay only for requests processed. Reserved capacity offers 20% discount for one year or 30% for three years.

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.

CosmosDB: Can I change my pricing model after choosing one?

No. Once you select a compute pricing model and API, they cannot be changed. This choice is permanent for that database.

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.

CosmosDB: Is there a trial period for Cosmos DB beyond the free tier?

Azure offers a 30-day free trial account for all Azure services. Additionally, Azure AI customers may be eligible for a 90-day free Cosmos DB subscription through the Azure AI Advantage program.

Source
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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