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Databases · head to head

BigQuery vs PostHog

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
PostHog logo

PostHog

Technology

The single platform to analyze, test, observe, and deploy new features

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.; PostHog the free tier covers 1M events, 5K web session recordings and 2.5K mobile recordings per month before usage-based billing starts
  • They diverge on capability: BigQuery covers Serverless compute, PostHog covers Product analytics.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and PostHog actually diverge.

Attributes where BigQuery and PostHog differ
AttributeBigQueryPostHog
PlatformsWeb, Cloud APIWeb, Ios, Android, Api
CategoryDatabasesTechnology
Founded20082020

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 PostHog

  • Product analytics
  • Session recording
  • Feature flags
  • A/B testing
  • Heatmaps
  • SQL access
  • Data warehouse
  • Apps platform

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

PostHog

  • Product analyticsnot BigQuery
  • Feature experimentationnot BigQuery
  • User behavior trackingnot BigQuery
  • A/B testingnot BigQuery
  • Debug production issuesnot 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.

PostHog

  • The free tier covers 1M events, 5K web session recordings and 2.5K mobile recordings per month before usage-based billing starts
  • Accounts without a card on file are limited to 1 project; adding one raises it to 6
  • Data retention is 1 year until a card is added, which extends it to 7 years
  • Support is community-only until the account is on a paid plan
  • Error tracking is capped at 100K exceptions and surveys at 1500 responses per month on the free tier

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

PostHog

Free
  • FreeFree
    • 1M events/month
    • 5K sessions/month
    • Unlimited users
  • Paid$undefined/month
    • $0.00031/event
    • $0.005/session
    • Advanced permissions
  • Enterprise$undefined/month
    • SAML SSO
    • Advanced security
    • 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 PostHog if

  • You need product analytics.
  • You want to start without paying.
  • You work on Web, Ios, Android, Api.
  • You also want session recording.
PostHog review

Questions people ask

Is BigQuery or PostHog better?
Neither clearly leads. BigQuery starts at Free and PostHog at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or PostHog?
BigQuery starts at Free and PostHog at Free.
Does BigQuery or PostHog run on more platforms?
BigQuery runs on Web, Cloud API. PostHog runs on Web, Ios, Android, Api.
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 PostHog is typically brought in for.
What can BigQuery do that PostHog cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. PostHog covers Product analytics, Session recording, Feature flags, A/B testing.

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.

PostHog: What does PostHog's free tier include per month?

PostHog free tier includes: 1M analytics events, 5K session replays, 1M feature flag requests, 100K error tracking exceptions, 1,500 survey responses, 1M data warehouse rows, 10K data pipeline events, 100K AI observability events, 500 PostHog AI credits, 10K workflow messages, and 10GB log ingestion. Source: https://posthog.com/pricing

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.

PostHog: How much data retention does PostHog provide on paid plans?

PostHog free tier provides 1-year data retention. Pay-as-you-go plans offer 7-year data retention across all projects, enabling longer historical analysis. Source: https://posthog.com/pricing

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.

PostHog: What percentage of PostHog users stay on the free tier?

PostHog states that 97% of companies use PostHog for free, indicating extensive free tier adoption. However, specific per-unit pricing rates for overages on paid plans are not published. Source: https://posthog.com/pricing

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.

PostHog: When does PostHog provide priority support on paid plans?

PostHog provides email or Slack support for accounts exceeding $2,000/month on pay-as-you-go plans. Specific response times and support SLAs are not detailed on their pricing page. Source: https://posthog.com/pricing

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.

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