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Databases · head to head

BigQuery vs Hex

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
Hex logo

Hex

Business Intelligence

AI-powered analytics platform unifying notebooks, dashboards, and business intelligence

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.; Hex pricing based per-seat ($36-$75/editor/month) becomes expensive for large teams
  • They diverge on capability: BigQuery covers Serverless compute, Hex covers Agentic notebooks.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Hex actually diverge.

Attributes where BigQuery and Hex differ
AttributeBigQueryHex
Pricing modelusage-basedSeat-based subscription with credit system
PlatformsWeb, Cloud APIWeb, Slack
CategoryDatabasesBusiness Intelligence
Founded20082019

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 Hex

  • Agentic notebooks
  • Conversational analytics
  • Data apps
  • Context Studio
  • Data warehouse integration
  • dbt integration
  • Version history
  • Scheduled automation

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

Hex

  • Deep exploratory analysis by data teams on organizational datasetsnot BigQuery
  • Self-serve analytics for business users without SQL knowledgenot BigQuery
  • Executive dashboarding and reporting with real-time datanot BigQuery
  • Cross-functional data collaboration and insight sharingnot BigQuery
  • AI-assisted analysis reducing manual exploration timenot 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.

Hex

  • Pricing based per-seat ($36-$75/editor/month) becomes expensive for large teams
  • Free Community tier limited to small compute and trial AI features
  • Advanced compute adds per-hour fees ($0.32-$4.06/hour), requiring cost monitoring
  • Learning curve for users unfamiliar with SQL or Python notebooks
  • Enterprise features requiring custom quotes lack transparent pricing

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

Hex

Free
  • CommunityFree
    • Hex agent trial
    • Data source connections
    • All cell types
  • Professional$36/month
    • Everything in Community
    • Full Hex agent access
    • Standard credits
  • Team$75/month
    • Everything in Professional
    • Extended credits
    • Unlimited published apps
  • Enterprise$undefined/custom
    • Everything in Team
    • Explorer seat add-ons
    • Audit logs

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 Hex if

  • You need agentic notebooks.
  • You want to start without paying.
  • You work on Web, Slack.
  • You also want conversational analytics.
Hex review

Questions people ask

Is BigQuery or Hex better?
Neither clearly leads. BigQuery starts at Free and Hex at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Hex?
BigQuery starts at Free and Hex at Free.
Does BigQuery or Hex run on more platforms?
BigQuery runs on Web, Cloud API. Hex runs on Web, Slack.
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 Hex is typically brought in for.
What can BigQuery do that Hex cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Hex covers Agentic notebooks, Conversational analytics, Data apps, Context Studio.

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.

Hex: What is included in the free Community plan?

The Community plan ($0) includes Hex agent trial, data source connections, all cell types, and small compute sizing. It's suitable for prototyping and hobbyist projects.

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.

Hex: How much do advanced compute resources cost?

Advanced compute is billed per minute and ranges from $0.32 to $4.06 per hour depending on resource tier. Monthly credit grants are included in paid plans.

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.

Hex: Can I share analytics with non-Hex users?

Yes. Published apps can be shared publicly. Embedded analytics are available on Enterprise plans for integrating Hex into other applications.

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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