Softwr

Databases · head to head

BigQuery vs Snowplow

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
Snowplow logo

Snowplow

Business Intelligence

Behavioural data pipeline you run in your own cloud, relicensed away from Apache 2.0 in 2024

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only BigQuery has a free tier, so it costs nothing to try first.
  • 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.; Snowplow the core pipeline was relicensed from Apache 2.0 on 8 January 2024 to the Snowplow Limited Use Licence Agreement and a Confluent-derived community licence, so organisations that adopted it as permissively licensed software must now review their entitlement, buy a licence, or migrate.
  • They diverge on capability: BigQuery covers Serverless compute, Snowplow covers Own-cloud deployment.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which BigQuery and Snowplow actually diverge.

Attributes where BigQuery and Snowplow differ
AttributeBigQuerySnowplow
Starting priceFreeOn request
Pricing modelusage-basedquote
Free tierYesNo
PlatformsWeb, Cloud APILinux, Web, Docker
CategoryDatabasesBusiness Intelligence
Founded2008Unknown

Identical on both: 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 Snowplow

  • Own-cloud deployment
  • Schema enforcement
  • Warehouse loading
  • Enrichment
  • Trackers
  • Streaming output
  • Data models
  • Snowplow BDP

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

Snowplow

  • A data team that needs full-fidelity event data in its own warehouse to build attribution or machine learning features rather than to populate dashboardsnot BigQuery
  • A regulated business that cannot send behavioural data to a third-party analytics vendor and must keep collection inside its own cloud accountnot BigQuery
  • A product organisation tired of silently malformed events, which wants a schema contract enforced at collection timenot BigQuery
  • A company modelling customer behaviour across web, mobile and server events that needs them in one consistent structurenot 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.

Snowplow

  • The core pipeline was relicensed from Apache 2.0 on 8 January 2024 to the Snowplow Limited Use Licence Agreement and a Confluent-derived community licence, so organisations that adopted it as permissively licensed software must now review their entitlement, buy a licence, or migrate.
  • You run the pipeline in your own cloud, which means the infrastructure bill, the on-call rota and the upgrade work are yours, and at high event volume that operational cost frequently exceeds what a hosted product would have charged.
  • Schema enforcement is the main benefit and the main friction, because every new event requires a schema to be authored and versioned, and teams without discipline around that end up blocked on their own governance process.
  • There is no analysis layer: Snowplow delivers data to your warehouse and nothing else, so you still need modelling, a BI tool and the people to run them before anyone sees a number.
  • The licence change fractured the community, spawning an Apache 2.0 fork, which means community contributions and third-party tooling are now split across two codebases with uncertain long-term maintenance.

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

Snowplow

On request
  • Snowplow BDP$undefined/year
    • Commercial pricing quoted by event volume and deployment
    • Core pipeline components under the Snowplow Limited Use Licence Agreement, not Apache 2.0
    • Trackers, analytics SDKs and Iglu SDKs remain Apache 2.0

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 Snowplow if

  • You need own-cloud deployment.
  • You work on Linux, Web, Docker.
  • You also want schema enforcement.
Snowplow review

Questions people ask

Is BigQuery or Snowplow better?
Neither clearly leads. BigQuery starts at Free and Snowplow at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Snowplow?
BigQuery has a free tier; the other does not. Paid plans start at Free for BigQuery and On request for Snowplow.
Does BigQuery or Snowplow run on more platforms?
BigQuery runs on Web, Cloud API. Snowplow runs on Linux, Web, Docker.
Can I use BigQuery for free?
Yes. BigQuery has a free tier, so you can try it without paying. Snowplow starts at On request.
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 Snowplow is typically brought in for.
What can BigQuery do that Snowplow cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Snowplow covers Own-cloud deployment, Schema enforcement, Warehouse loading, Enrichment.

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.

Snowplow: Is Snowplow still open source?

Not in the permissive sense. On 8 January 2024 the core pipeline moved from Apache 2.0 to the Snowplow Limited Use Licence Agreement, with version 1.1 following in December 2024, alongside a community licence based on the Confluent Community Licence. Trackers and analytics SDKs remain Apache 2.0.

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.

Snowplow: Can we still run it for free in production?

Free use of the relicensed core components is materially constrained and commercial use generally requires an agreement. Read the current licence text against your intended use rather than relying on older documentation.

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.

Snowplow: Is there an Apache 2.0 alternative?

Yes, a fork called OpenSnowcat was created in response to the relicensing and continues under Apache 2.0.

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.

Snowplow: What does Snowplow BDP cost?

Not published. It is quoted by event volume and deployment, and your own cloud infrastructure costs are separate and additional.

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.

Share

Related pages

More on BigQuery

More on Snowplow

Keep looking

Other head to heads