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Databases · head to head

BigQuery vs Hookdeck

BigQuery logo

BigQuery

Databases

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

From
Free
Free plan
Yes
Visit BigQueryFull review
Hookdeck logo

Hookdeck

Developer Tools

Event gateway that receives, queues, retries and replays inbound webhooks

From
Free
Free plan
Yes
Visit HookdeckFull review

The short version

  • Free plans on both; paid from $6.25/mo and $39/mo.
  • Only BigQuery lists serverless compute; only Hookdeck lists ingest and persist.
  • Where Hookdeck falls short: pricing meters delivered events, so fan-out multiplies the bill: one inbound event routed to four services counts as four deliveries.
  • Prices and features on this page were last checked on 31 August 2026.

Where they differ

Only the attributes on which BigQuery and Hookdeck actually diverge.

Attributes where BigQuery and Hookdeck differ
AttributeBigQueryHookdeck
Pricing modelUsage-basedPer month by delivered event count
PlatformsWeb, APIWeb, Linux, macOS, Windows
CategoryDatabasesDeveloper Tools

Identical on both: starting price (Free), free tier (Yes).

Not yet recorded: founded for Hookdeck.

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 Hookdeck

  • Ingest and persist
  • Automatic retries
  • Filters and fan-out
  • Transformations
  • Local development CLI
  • Rate limiting

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

Hookdeck

  • A payments integration where losing a Stripe event during a deploy causes an order to go unfulfillednot BigQuery
  • Fanning one provider webhook out to several internal services without each subscribing separatelynot BigQuery
  • Debugging a partner integration by replaying the exact failing payload after shipping a fixnot BigQuery
  • Receiving production-shaped webhooks on a developer laptop without running a public tunnelnot 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

Hookdeck

  • Pricing meters delivered events, so fan-out multiplies the bill: one inbound event routed to four services counts as four deliveries
  • Free-tier retention is three days, which is shorter than the time it typically takes to notice a failing integration, so the payloads needed for a replay are often already gone
  • It becomes a single point of failure in front of every third-party integration, and an outage there means every provider webhook queues or fails at once
  • The transformation layer runs JavaScript in a constrained environment, so anything that needs a database lookup or an external call has to happen downstream instead
  • For a team already running Kafka or SQS the value is mostly the console and the replay UI, which is a hard cost to justify against infrastructure they already operate

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

Hookdeck

Free
  • DeveloperFree
    • Up to ten thousand events per month
    • Three-day retention
    • One user
  • Team$39/mo
    • Ten thousand events included
    • Unlimited users
    • Pay as you go metering above the included events
  • Growth$499/mo
    • Ten thousand events included plus metered usage
    • Thirty-day retention
    • Uptime and latency SLAs
  • EnterpriseOn request
    • Negotiated event volume
    • Custom retention
    • Dedicated support

Which should you pick?

Choose BigQuery if

  • You need serverless compute.
  • You want to start without paying.
  • You work on Web, API.
  • You also want separation of storage and compute.
BigQuery review

Choose Hookdeck if

  • You need ingest and persist.
  • You want to start without paying.
  • You work on Web, Linux, macOS, Windows.
  • You also want automatic retries.
Hookdeck review

Questions people ask

Is BigQuery or Hookdeck better?
Neither clearly leads. BigQuery starts at Free and Hookdeck at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Hookdeck?
BigQuery starts at Free and Hookdeck at Free.
Does BigQuery or Hookdeck run on more platforms?
BigQuery runs on Web, API. Hookdeck runs on Web, Linux, macOS, Windows.
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 Hookdeck is typically brought in for.
What can BigQuery do that Hookdeck cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Hookdeck covers Ingest and persist, Automatic retries, Filters and fan-out, Transformations.

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.

Hookdeck: Is there a free plan?

Yes, ten thousand events a month with three-day retention and one user.

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.

Hookdeck: How is usage counted?

By delivered events, so a single inbound webhook fanned out to three destinations counts as three.

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.

Hookdeck: Can I replay a failed webhook?

Yes, individually or in bulk from the console, with the original payload.

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.

Hookdeck: Does it work for outbound webhooks too?

Yes, the same queueing, retry and observability applies to webhooks you send.

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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