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Databases · head to head

BigQuery vs Okteto

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
Okteto logo

Okteto

Developer Tools

Runs production-like development environments on your own Kubernetes cluster

From
Free
Free plan
Yes
Visit OktetoFull review

The short version

  • Okteto is free; BigQuery starts at $6.25/mo.
  • Only BigQuery lists serverless compute; only Okteto lists cluster development environments.
  • Prices and features on this page were last checked on 31 August 2026.

Where they differ

Only the attributes on which BigQuery and Okteto actually diverge.

Attributes where BigQuery and Okteto differ
AttributeBigQueryOkteto
Pricing modelUsage-basedQuote
PlatformsWeb, APILinux, macOS, Windows, API, Self-hosted, Web
CategoryDatabasesDeveloper Tools

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

Not yet recorded: founded for Okteto.

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 Okteto

  • Cluster development environments
  • File synchronisation
  • Development containers
  • Environment catalogue
  • Preview environments
  • Bring your own cloud

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

Okteto

  • A microservices estate where no developer can run the full dependency graph on a laptopnot BigQuery
  • Giving each pull request a working environment reviewers can click rather than describenot BigQuery
  • Letting coding agents build and test against real databases and queues instead of mocksnot BigQuery
  • Removing a fleet of local Kubernetes installations that drift from production and produce false test resultsnot 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

Okteto

  • Two of the three plans publish no price at all, with no currency and no billing period stated anywhere, so any budget above five seats requires a sales conversation before you can even compare it with an alternative
  • The Apache-2.0 CLI is restricted to the development section of the manifest, so build services, user management and observability all require the commercial platform and the open licence provides very little continuity insurance
  • The last disclosed funding round is a 15 million US dollar Series A from February 2022 with nothing announced since, and the contributor base is dominated by company employees, which is concentrated risk for something embedded in every developer daily loop
  • You must bring and pay for the Kubernetes cluster, so node cost, capacity planning and version upgrades stay with your platform team on top of the licence fee
  • The 2026 repositioning towards AI agents means the classic developer inner loop is no longer what the marketing leads with, so a buyer purchasing that use case should confirm roadmap commitment rather than assume it

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

Okteto

Free
  • StarterFree
    • 5 seats included
    • Self-hosted deployment into your own cluster
    • Community support
  • ScaleOn request
    • Contact sales, no price, currency or billing period published
    • More seats and environments than Starter
    • Self-hosted deployment
  • EnterpriseOn request
    • Contact sales, no price published
    • Bring your own cloud deployment
    • Available through Google Cloud and AWS marketplaces

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 Okteto if

  • You need cluster development environments.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, API, Self-hosted, Web.
  • You also want file synchronisation.
Okteto review

Questions people ask

Is BigQuery or Okteto better?
Neither clearly leads. BigQuery starts at Free and Okteto at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Okteto?
BigQuery starts at Free and Okteto at Free.
Does BigQuery or Okteto run on more platforms?
BigQuery runs on Web, API. Okteto runs on Linux, macOS, Windows, API, Self-hosted, Web.
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 Okteto is typically brought in for.
What can BigQuery do that Okteto cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Okteto covers Cluster development environments, File synchronisation, Development containers, Environment catalogue.

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.

Okteto: Is Okteto open source?

The CLI is Apache-2.0, but the README states it supports only the development section of the manifest. Everything operationally interesting, including builds, user management and observability, is in the commercial platform.

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.

Okteto: What does it cost?

Only the free Starter tier with five seats is published. Scale and Enterprise are both contact sales, with no price, currency or billing period disclosed on the pricing page.

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.

Okteto: Do I need my own Kubernetes cluster?

Yes. Okteto installs into a cluster you provide and pay for, so capacity, upgrades and node costs remain your responsibility in addition to the licence.

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.

Okteto: How is this different from running Kubernetes locally?

Environments run against the same managed databases, queues and service mesh as production, so a class of failures that only appears in a real cluster is caught before merge rather than after deploy.

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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