Is BigQuery or Firebolt better?

Neither clearly leads. BigQuery starts at Free and Firebolt at $1.84/hour, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.

Which is cheaper, BigQuery or Firebolt?

BigQuery has a free tier; the other does not. Paid plans start at Free for BigQuery and $1.84/hour for Firebolt.

Does BigQuery or Firebolt run on more platforms?

BigQuery runs on Web, Cloud API. Firebolt runs on Cloud (AWS, GCP, Azure preview), Docker, Kubernetes.

Can I use BigQuery for free?

Yes. BigQuery has a free tier, so you can try it without paying. Firebolt starts at $1.84/hour.

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 Firebolt is typically brought in for.

What can BigQuery do that Firebolt cannot?

BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Firebolt covers Sub-second Queries, Sparse Indexes, Data Pruning, Decoupled Storage/Compute.

Databases · head to head

BigQuery vs Firebolt

BigQuery

Databases

Google Cloud's serverless analytical warehouse, billed either by bytes scanned per query or by reserved compute slots.

From: Free
Rated: -

Full review Website

Firebolt

Databases

Sub-second analytics at cloud data warehouse scale

From: $1.84/hour
Rated: -

Full review Website

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.; Firebolt compute billed per second on Arm-based processors; small instances still incur measurable costs during idle periods despite auto-stop
They diverge on capability: BigQuery covers Serverless compute, Firebolt covers Sub-second Queries.
Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Firebolt actually diverge.

Attributes where BigQuery and Firebolt differ
Attribute	BigQuery	Firebolt
Starting price	Free	$1.84/hour
Free tier	Yes	No
Platforms	Web, Cloud API	Cloud (AWS, GCP, Azure preview), Docker, Kubernetes
Founded	2008	2019

Identical on both: pricing model (usage-based), user rating (Not yet rated), category (Databases).

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 Firebolt

Sub-second Queries
Sparse Indexes
Data Pruning
Decoupled Storage/Compute
SQL Support
Semi-structured Data
Workload Isolation
Airflow

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

Firebolt

Data analytics teams running gigabyte-to-petabyte datasets with sub-second query requirementsnot BigQuery
Real-time business intelligence platforms requiring ACID transactions and snapshot isolationnot BigQuery
Applications needing vector search on analytical data for similarity queriesnot 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.

Firebolt

Compute billed per second on Arm-based processors; small instances still incur measurable costs during idle periods despite auto-stop
Storage pass-through charged at $0.0264/GB monthly on compressed data; uncompressed storage could exceed this
Azure deployment currently in Preview status; production recommendations unclear
Vector indexes limited to float arrays; other data types require alternative indexing strategies
Free tier credits ($200) limited; no perpetual free tier for production use

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

Firebolt

$1.84/hour

No published plan breakdown. See the Firebolt review.

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 Firebolt if

You need sub-second queries.
You work on Cloud (AWS, GCP, Azure preview), Docker, Kubernetes.
You also want sparse indexes.

Firebolt review

Questions people ask

Is BigQuery or Firebolt better?: Neither clearly leads. BigQuery starts at Free and Firebolt at $1.84/hour, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Firebolt?: BigQuery has a free tier; the other does not. Paid plans start at Free for BigQuery and $1.84/hour for Firebolt.
Does BigQuery or Firebolt run on more platforms?: BigQuery runs on Web, Cloud API. Firebolt runs on Cloud (AWS, GCP, Azure preview), Docker, Kubernetes.
Can I use BigQuery for free?: Yes. BigQuery has a free tier, so you can try it without paying. Firebolt starts at $1.84/hour.
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 Firebolt is typically brought in for.
What can BigQuery do that Firebolt cannot?: BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Firebolt covers Sub-second Queries, Sparse Indexes, Data Pruning, Decoupled Storage/Compute.

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.

Firebolt: How does Firebolt's compute billing model work?

Firebolt uses per-second billing with scale-to-zero capability. The smallest S tier costs $1.84 per hour with 8 vCPU and 64GB memory, while the largest 4XL tier costs $58.88 per hour with 256 vCPU. Users only pay when compute is running.

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.

Firebolt: What is the cost for data storage on Firebolt?

Storage costs $0.0264 per GB per month on object storage, billed as pass-through cost at cloud provider rates.

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.

Firebolt: What free credits or trial does Firebolt offer new users?

New users receive $200 free credits to get started with the platform.

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.

Firebolt: Does Firebolt publish pricing for commitment-based discounts?

The pricing FAQ lists a question about commitment-based discounts but does not provide published answers on the pricing page. This requires direct inquiry with sales.

Source

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.

Firebolt: What deployment options does Firebolt offer besides managed service?

Firebolt offers self-hosted open source deployment (unlimited) and Bring Your Own Cloud (BYOC) options in addition to managed service.

Source

BigQuery vs Firebolt

BigQuery

Firebolt

The short version

Where they differ

What each one covers

Only in BigQuery

Only in Firebolt

What people use each for

BigQuery

Firebolt

Where each one falls short

BigQuery

Firebolt

Pricing, plan by plan

BigQuery

Firebolt

Which should you pick?

Choose BigQuery if

Choose Firebolt if

Questions people ask

Answered from the vendors’ own pages

Related pages

More on BigQuery

More on Firebolt

Keep looking

Other head to heads