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Databases · head to head

BigQuery vs PartyKit

BigQuery logo

BigQuery

Databases

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

From
Free
Free plan
Yes
Visit BigQueryFull review
P

PartyKit

Developer Tools

Platform for building and deploying realtime multiplayer servers on the edge

From
Free
Free plan
Yes
Visit PartyKitFull review

The short version

  • PartyKit is free; BigQuery starts at $6.25/mo.
  • Only BigQuery lists serverless compute; only PartyKit lists stateful edge servers.
  • Where PartyKit falls short: documentation and FAQ material on the marketing site is sparse compared to larger realtime platforms.
  • Prices and features on this page were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and PartyKit actually diverge.

Attributes where BigQuery and PartyKit differ
AttributeBigQueryPartyKit
Pricing modelUsage-basedFreemium
CategoryDatabasesDeveloper Tools

Identical on both: starting price (Free), free tier (Yes), platforms (Web, API).

Not yet recorded: founded for PartyKit.

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 PartyKit

  • Stateful edge servers
  • WebSocket-first API
  • CRDT library compatibility
  • Framework integrations
  • Global edge deployment
  • Custom domains

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

PartyKit

  • Multiplayer collaborative appsnot BigQuery
  • Realtime AI agent backendsnot BigQuery
  • Live cursors and presencenot BigQuery
  • Collaborative whiteboards and documentsnot 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

PartyKit

  • Documentation and FAQ material on the marketing site is sparse compared to larger realtime platforms
  • Commercial free tier requires deploying to the user's own Cloudflare account, adding setup complexity
  • Storage on the free Individual plan clears every 24 hours, limiting it to prototyping rather than persistent production data
  • Smaller ecosystem and community than more established realtime infrastructure providers

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

PartyKit

Free
  • IndividualFree
    • Up to 10 live projects
    • Deploy to the global edge platform
    • Storage clears every 24 hours
  • CommercialFree
    • Unlimited projects
    • Custom domains
    • Runs on your own Cloudflare account; pay only Cloudflare usage

Which should you pick?

Choose BigQuery if

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

Choose PartyKit if

  • You need stateful edge servers.
  • You want to start without paying.
  • You work on Web, API.
  • You also want websocket-first api.
PartyKit review

Questions people ask

Is BigQuery or PartyKit better?
Neither clearly leads. BigQuery starts at Free and PartyKit at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or PartyKit?
BigQuery starts at Free and PartyKit at Free.
Does BigQuery or PartyKit run on more platforms?
Both run on Web, API, so platform support will not decide this one for you.
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 PartyKit is typically brought in for.
What can BigQuery do that PartyKit cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. PartyKit covers Stateful edge servers, WebSocket-first API, CRDT library compatibility, Framework integrations.

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.

PartyKit: How much does PartyKit cost?

PartyKit is completely free. Both the Individual and Commercial plans have no upfront costs.

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.

PartyKit: What is PartyKit's Individual plan?

The Individual plan is free and includes deployment to a global edge platform, support for up to 10 live projects, and is suitable for small projects. Storage is cleared every 24 hours.

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.

PartyKit: What is PartyKit's Commercial plan?

The Commercial plan is free but requires deploying to your own Cloudflare account. It includes custom domains, unlimited projects, and you pay only your Cloudflare usage costs.

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.

PartyKit: Can I upgrade from Individual to Commercial plan?

Yes, both plans are free but offer different feature sets. The Commercial plan removes project restrictions but requires managing your own Cloudflare infrastructure.

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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