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Databases · head to head

BigQuery vs Blacksmith

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
Blacksmith logo

Blacksmith

Developer Tools

2x faster GitHub Actions with 60% cost savings

From
Free
Free plan
Yes
Visit BlacksmithFull review

The short version

  • Blacksmith is a GitHub Actions runner service.
  • Free plans on both; paid from $6.25/mo and $0.004/mo.
  • Only BigQuery lists serverless compute; only Blacksmith lists bare metal runners.
  • Where Blacksmith falls short: per-minute pricing model requires estimating usage to predict costs.
  • Prices and features on this page were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Blacksmith actually diverge.

Attributes where BigQuery and Blacksmith differ
AttributeBigQueryBlacksmith
PlatformsWeb, APIGitHub Actions, Linux, Windows, macOS
CategoryDatabasesDeveloper Tools

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

Not yet recorded: pricing model for Blacksmith, founded for Blacksmith.

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 Blacksmith

  • Bare metal runners
  • Multiple OS support
  • ARM support
  • Docker layer caching
  • Sticky disks
  • GitHub Actions observability
  • Free tier
  • Static IPs

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

Blacksmith

  • Replacing GitHub Actions runners with faster, cheaper infrastructurenot BigQuery
  • Accelerating CI build times for organizations with heavy CI loadnot BigQuery
  • Reducing cloud spend on GitHub Actions by 60% or morenot BigQuery
  • Supporting ARM architecture builds without GitHub runnersnot 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

Blacksmith

  • Per-minute pricing model requires estimating usage to predict costs
  • macOS M4 pricing ($0.08/min) is significantly higher than GitHub Actions
  • Docker layer caching and sticky disks are paid add-ons at $0.50/GB/mo
  • Static IP add-on costs $100/IP/mo

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

Blacksmith

Free
  • Ubuntu x64$0.004/minute
    • 3,000 free minutes per month
    • 2x faster hardware
    • 4x faster cache downloads
  • Ubuntu ARM$0.0025/minute
    • 3,000 free minutes per month
    • 2x faster hardware
    • 4x faster cache downloads
  • Windows x64$0.008/minute
    • 3,000 free minutes per month
    • 2x faster hardware
    • 4x faster cache downloads
  • macOS M4$0.08/minute
    • 3,000 free minutes per month
    • 2x faster hardware
    • 4x faster cache downloads

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 Blacksmith if

  • You need bare metal runners.
  • You want to start without paying.
  • You work on GitHub Actions, Linux, Windows, macOS.
  • You also want multiple os support.
Blacksmith review

Questions people ask

Is BigQuery or Blacksmith better?
Neither clearly leads. BigQuery starts at Free and Blacksmith at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Blacksmith?
BigQuery starts at Free and Blacksmith at Free.
Does BigQuery or Blacksmith run on more platforms?
BigQuery runs on Web, API. Blacksmith runs on GitHub Actions, Linux, Windows, macOS.
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 Blacksmith is typically brought in for.
What can BigQuery do that Blacksmith cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Blacksmith covers Bare metal runners, Multiple OS support, ARM support, Docker layer caching.

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.

Blacksmith: How much do Blacksmith runners cost compared to GitHub Actions?

Blacksmith offers 60-75% cost savings depending on OS. Ubuntu x64 costs $0.004/min vs GitHub at $0.012/min. All plans include 3,000 free minutes monthly.

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.

Blacksmith: Can I use Docker layer caching with Blacksmith?

Yes, Docker layer caching is available as an add-on at $0.50/GB/mo. Managed Docker layer persistence is included with the base service.

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.

Blacksmith: What is the SLA for Enterprise plans?

Enterprise Blacksmith plans include a 99.9% SLA guarantee along with 24/7 priority support, dedicated Slack channels, white-glove onboarding, and CI optimization support.

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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