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Databases · head to head

BigQuery vs Fivetran

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
Fivetran logo

Fivetran

Automation Integration

The most trusted data movement platform

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.; Fivetran billed on monthly active rows, so the bill tracks how much source data changes rather than how much is stored or queried
  • They diverge on capability: BigQuery covers Serverless compute, Fivetran covers Automated data pipeline.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Fivetran actually diverge.

Attributes where BigQuery and Fivetran differ
AttributeBigQueryFivetran
PlatformsWeb, Cloud APIWeb, Cloud
CategoryDatabasesAutomation Integration
Founded20082012

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 Fivetran

  • Automated data pipeline
  • Change Data Capture
  • Data transformation
  • Real-time sync
  • Monitoring
  • Data quality
  • Scheduling
  • Notifications

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

Fivetran

  • Managed data pipelines from SaaS sources into a warehousenot BigQuery
  • Keeping a warehouse in sync with production databases without writing connectorsnot 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.

Fivetran

  • Billed on monthly active rows, so the bill tracks how much source data changes rather than how much is stored or queried
  • Each connection follows its own cost curve, so total spend is hard to predict before running a pipeline
  • The free plan allows 500,000 monthly active rows, 3,500 activation rows and 5,000 model runs
  • Transformations are metered separately, from $0.01 per model run above 5,000 down to $0.002 above 100,000
  • A schema change upstream that touches many rows raises the bill without any change on the customer's side

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

Fivetran

Free
  • FreeFree
    • Limited connectors
    • Basic support
  • Standard$300/month
    • 500+ connectors
    • Priority support
  • Enterprise$1000/month
    • Custom connectors
    • Dedicated support

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 Fivetran if

  • You need automated data pipeline.
  • You want to start without paying.
  • You work on Web, Cloud.
  • You also want change data capture.
Fivetran review

Questions people ask

Is BigQuery or Fivetran better?
Neither clearly leads. BigQuery starts at Free and Fivetran at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Fivetran?
BigQuery starts at Free and Fivetran at Free.
Does BigQuery or Fivetran run on more platforms?
BigQuery runs on Web, Cloud API. Fivetran runs on Web, Cloud.
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 Fivetran is typically brought in for.
What can BigQuery do that Fivetran cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Fivetran covers Automated data pipeline, Change Data Capture, Data transformation, Real-time sync.

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.

Fivetran: What does Fivetran's free plan include?

The free plan includes 500,000 monthly active rows for connections, 3,500 monthly active rows for activations, and 5,000 monthly model runs for transformations.

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.

Fivetran: What is the trial period for Fivetran?

Fivetran offers a 14-day risk-free trial for new accounts. Each new connection also includes 14 days of free use, with trial extensions available by contacting support.

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.

Fivetran: How much do I save by paying annually instead of monthly?

Annual contracts save up to 22.6% compared to monthly pricing, with tiered discounts starting at 5% and increasing based on annual list price.

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.

Fivetran: Can I cancel or modify my Fivetran subscription anytime?

Plans can be upgraded at any time. Connections can be added or removed at any time, and you can block tables or schemas to reduce usage. Downgrade or cancellation policies are not specified on the pricing page.

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.

Fivetran: What is the pricing for Fivetran transformations?

Transformations cost $0.01 per run for 5,001 to 30,000 monthly runs, with per-run costs declining as volume increases.

Source
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