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Databases · head to head

BigQuery vs Linode

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
Linode logo

Linode

Cloud

Affordable cloud hosting and infrastructure

From
Free
Rated
-
Full reviewWebsite

The short version

  • 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.; Linode linode.com/pricing returns a 301 redirect to akamai.com/cloud/pricing; the service is now sold as Akamai Cloud
  • They diverge on capability: BigQuery covers Serverless compute, Linode covers Compute instances.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Linode actually diverge.

Attributes where BigQuery and Linode differ
AttributeBigQueryLinode
PlatformsWeb, Cloud APIWeb, Api, Cli
CategoryDatabasesCloud
Founded20082003

Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), 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 Linode

  • Compute instances
  • Object storage
  • Block storage
  • Kubernetes
  • Managed database
  • Load balancers
  • Firewalls
  • Private networks

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

Linode

  • Running Linux virtual machines on hourly billed shared or dedicated CPU plansnot BigQuery
  • Managed Kubernetes, block storage and object storage on a single cloud accountnot BigQuery
  • Hosting workloads in a specific one of the listed global regionsnot 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.

Linode

  • linode.com/pricing returns a 301 redirect to akamai.com/cloud/pricing; the service is now sold as Akamai Cloud
  • Charges accrue for any service on the account even when it is powered off, because RAM and network capacity stay reserved; only deleting the service stops billing
  • Network transfer beyond the monthly allotment is billed from $0.005 per GB and the rate varies by region
  • The Akamai Cloud pricing landing page shows no rates and directs visitors to regional pricing pages or sales

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

Linode

Free
  • Nanode 1GB$5/month
    • 1GB RAM
    • 1 vCPU
    • 25GB SSD
  • Linode 4GB$20/month
    • 4GB RAM
    • 2 vCPU
    • 80GB SSD

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 Linode if

  • You need compute instances.
  • You want to start without paying.
  • You work on Web, Api, Cli.
  • You also want object storage.
Linode review

Questions people ask

Is BigQuery or Linode better?
Neither clearly leads. BigQuery starts at Free and Linode at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Linode?
BigQuery starts at Free and Linode at Free.
Does BigQuery or Linode run on more platforms?
BigQuery runs on Web, Cloud API. Linode runs on Web, Api, Cli.
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 Linode is typically brought in for.
What can BigQuery do that Linode cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Linode covers Compute instances, Object storage, Block storage, Kubernetes.

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.

Linode: Does Linode charge for data egress?

Linode emphasizes transparent pricing with no egress surprises and a free egress allowance included in the service. The pricing is described as straightforward with no hidden fees and no vendor lock-in.

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.

Linode: What is the free trial credit amount?

New and existing enterprise customers can receive up to $5,000 in cloud credits through promotional offers.

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.

Linode: Is there vendor lock-in with Linode's pricing model?

No. Linode explicitly states there is no vendor lock-in as part of their transparent pricing approach.

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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