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Databases · head to head

BigQuery vs FullStory

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
FullStory logo

FullStory

E-Commerce

Digital experience intelligence 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.; FullStory free tier limited to 30,000 sessions per month, no 5,000+ monthly active user sites
  • They diverge on capability: BigQuery covers Serverless compute, FullStory covers Session replay.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and FullStory actually diverge.

Attributes where BigQuery and FullStory differ
AttributeBigQueryFullStory
Pricing modelusage-basedquote
PlatformsWeb, Cloud APIWeb, Mobile
CategoryDatabasesE-Commerce
Founded20082014

Identical on both: starting price (Free), 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 FullStory

  • Session replay
  • Heatmaps
  • Conversion funnels
  • User journey mapping
  • Error tracking
  • Frustration signals
  • Search functionality
  • Custom events

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

FullStory

  • User experience analysisnot BigQuery
  • Bug reproductionnot BigQuery
  • Conversion optimizationnot BigQuery
  • Customer supportnot BigQuery
  • Product developmentnot 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.

FullStory

  • Free tier limited to 30,000 sessions per month, no 5,000+ monthly active user sites
  • Personal email addresses cannot be used for signup; business email domain required
  • Paid plan pricing not publicly listed, requires sales contact for quotes
  • Free plan has no email support, only community-based assistance
  • Mobile app analytics requires a separate add-on purchase

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

FullStory

Free
  • FreeFree
    • 1,000 sessions/month
    • 14-day data retention
    • Basic analytics
  • Business$undefined/month
    • Custom sessions
    • 3-month retention
    • Advanced analytics
  • Enterprise$undefined/month
    • Unlimited sessions
    • Custom retention
    • Advanced privacy controls

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 FullStory if

  • You need session replay.
  • You want to start without paying.
  • You work on Web, Mobile.
  • You also want heatmaps.
FullStory review

Questions people ask

Is BigQuery or FullStory better?
Neither clearly leads. BigQuery starts at Free and FullStory at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or FullStory?
BigQuery starts at Free and FullStory at Free.
Does BigQuery or FullStory run on more platforms?
BigQuery runs on Web, Cloud API. FullStory runs on Web, Mobile.
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 FullStory is typically brought in for.
What can BigQuery do that FullStory cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. FullStory covers Session replay, Heatmaps, Conversion funnels, User journey mapping.

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.

FullStory: What does FullStory's free tier include?

30,000 sessions per month, 10 user seats, 5,000 server-side events per month, 1 year of session replay retention, and 1 year of product analytics retention. Session capture pauses when you exceed the monthly limit, though existing sessions remain accessible.

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.

FullStory: What features are excluded from the free plan?

Dashboards, configurable form privacy, Go-Live functionality, Streams, client-side rate hooks, mobile app analytics, and StoryAI are not available on the free tier. Email support is also unavailable; only community-based help is provided.

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.

FullStory: Can I use a personal email to sign up for FullStory's free plan?

No. FullStory requires a business email domain for signup; personal email services like Gmail cannot be used for free plan registration.

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.

FullStory: How does FullStory integrate with Slack?

FullStory's Slack integration allows individual users to send noteworthy sessions to Slack channels. Advanced and Enterprise plans can configure Alerts to receive notifications in Slack when user metrics exceed defined thresholds.

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.

FullStory: What analytics platforms does FullStory integrate with?

FullStory integrates with Segment, Mixpanel, Adobe Analytics, Google Analytics, Salesforce, HubSpot, and others. These integrations allow you to attach FullStory session URLs to events in your analytics platform for cross-platform correlation.

Source
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