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Databases · head to head

BigQuery vs Koyeb

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
Koyeb logo

Koyeb

Cloud

High-performance serverless infrastructure for APIs, inference, and databases

From
$29/month
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.; Koyeb pricing starts at $29/month with additional compute costs
  • They diverge on capability: BigQuery covers Serverless compute, Koyeb covers Serverless containers.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Koyeb actually diverge.

Attributes where BigQuery and Koyeb differ
AttributeBigQueryKoyeb
Starting priceFree$29/month
Pricing modelusage-basedUnknown
Free tierYesNo
PlatformsWeb, Cloud APIWeb, CLI, API
CategoryDatabasesCloud
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 Koyeb

  • Serverless containers
  • GPU support
  • Global distribution
  • Multi-protocol support
  • Serverless Postgres
  • Zero-downtime deployments

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

Koyeb

  • Deploying AI inference models globally with GPU accelerationnot BigQuery
  • Building SaaS platforms with automatic scalingnot BigQuery
  • Running distributed AI agents and background workersnot 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.

Koyeb

  • Pricing starts at $29/month with additional compute costs
  • GPU compute is expensive at $0.75-$2.50 per hour
  • Limited customization for infrastructure configuration

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

Koyeb

$29/month
  • Pro$29/month
    • $10 included compute
    • 10 users
    • 100 services
  • Scale$299/month
    • $100 included compute
    • 50 users
    • 1,000 services
  • Enterprise$1000/month
    • Unlimited users
    • Custom resources
    • SSO/RBAC

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 Koyeb if

  • You need serverless containers.
  • You work on Web, CLI, API.
  • You also want gpu support.
Koyeb review

Questions people ask

Is BigQuery or Koyeb better?
Neither clearly leads. BigQuery starts at Free and Koyeb at $29/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Koyeb?
BigQuery has a free tier; the other does not. Paid plans start at Free for BigQuery and $29/month for Koyeb.
Does BigQuery or Koyeb run on more platforms?
BigQuery runs on Web, Cloud API. Koyeb runs on Web, CLI, API.
Can I use BigQuery for free?
Yes. BigQuery has a free tier, so you can try it without paying. Koyeb starts at $29/month.
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 Koyeb is typically brought in for.
What can BigQuery do that Koyeb cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Koyeb covers Serverless containers, GPU support, Global distribution, Multi-protocol support.

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.

Koyeb: What are Koyeb's subscription plans?

Pro plan is $29/month with $10 included compute, Scale plan is $299/month with $100 included compute and 99.9% SLA, and Enterprise starts at $1,000/month with unlimited users and 99.99% SLA.

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.

Koyeb: How much does GPU compute cost?

GPU pricing is per-second: RTX-A6000 costs $0.75/hour, A100 costs $1.60/hour, H100 costs $2.50/hour, and 8x H100 costs $20.00/hour.

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.

Koyeb: What database options are available?

Koyeb offers serverless Postgres starting at free (0.25 vCPU, 1GB RAM) up to 3XL at $1.28/hour with 8 vCPU and 32GB RAM. Storage costs $0.50/month per GB.

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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