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Databases · head to head

BigQuery vs Knack

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
Knack logo

Knack

Databases

Hosted no-code database and web app builder priced by stored records and storage, with unlimited user accounts on every plan.

From
$59/month
Rated
-
Full reviewWebsite

The short version

  • Only BigQuery has a free tier, so it costs nothing to try first.
  • 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.; Knack plans are capped by stored records, so an application that logs events or keeps history rather than current state climbs tiers on data volume alone, and archiving old records becomes a permanent maintenance chore rather than a one-off.
  • They diverge on capability: BigQuery covers Serverless compute, Knack covers Visual database builder.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Knack actually diverge.

Attributes where BigQuery and Knack differ
AttributeBigQueryKnack
Starting priceFree$59/month
Pricing modelusage-basedsubscription
Free tierYesNo
PlatformsWeb, Cloud APIWeb
Founded2008Unknown

Identical on both: user rating (Not yet rated), category (Databases).

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 Knack

  • Visual database builder
  • User logins and roles
  • Page builder
  • Unlimited users
  • E-commerce
  • Automation flows
  • Scheduled tasks
  • REST API and webhooks

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

Knack

  • A member or client portal where thousands of external people need their own login and see only their own recordsnot BigQuery
  • Replacing a shared spreadsheet used by a team that has outgrown it but cannot justify a developer to build a bespoke internal toolnot BigQuery
  • Inventory, asset or case tracking for a small operations team that needs roles, forms and a record of who changed whatnot BigQuery
  • A registration or booking application for an association, school or non-profit where the user count is large and the record count stays modestnot 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.

Knack

  • Plans are capped by stored records, so an application that logs events or keeps history rather than current state climbs tiers on data volume alone, and archiving old records becomes a permanent maintenance chore rather than a one-off.
  • API access is capped per day, at 1,000 calls on the entry plan and 10,000 at the Corporate tier, so a scheduled sync or a busy automation can exhaust the day's quota before the working day ends and integrations then fail silently.
  • The application itself cannot be exported or self-hosted; records can be downloaded but the pages, roles, flows and business logic exist only inside Knack, so outgrowing the platform means rebuilding the app rather than moving it.
  • Customisation beyond the builder is limited to injected CSS and JavaScript that Knack's support does not cover, so any non-standard interface behaviour becomes yours to maintain against a DOM the vendor can change without warning.
  • Compliance capabilities that regulated buyers assume are baseline, HIPAA and GovCloud options, advanced SSO, IP restrictions and private environments, are gated to the Corporate and Enterprise tiers, so a small regulated pilot cannot legitimately start on an entry plan.

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

Knack

$59/month
  • Starter$59/month
    • 20,000 database records
    • Unlimited users, tables, fields
    • 25 AI credits
  • Pro$130/month
    • 50,000 database records
    • Remove Knack branding
    • E-commerce payments
  • Corporate$300/month
    • 125,000-2.5M database records
    • App restore functionality
    • Advanced SSO
  • Enterprise$null/month
    • Dedicated account manager
    • HIPAA/GovCloud-based options
    • Custom pricing

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 Knack if

  • You need visual database builder.
  • You also want user logins and roles.
Knack review

Questions people ask

Is BigQuery or Knack better?
Neither clearly leads. BigQuery starts at Free and Knack at $59/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Knack?
BigQuery has a free tier; the other does not. Paid plans start at Free for BigQuery and $59/month for Knack.
Does BigQuery or Knack run on more platforms?
BigQuery runs on Web, Cloud API. Knack runs on Web.
Can I use BigQuery for free?
Yes. BigQuery has a free tier, so you can try it without paying. Knack starts at $59/month.
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 Knack is typically brought in for.
What can BigQuery do that Knack cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Knack covers Visual database builder, User logins and roles, Page builder, Unlimited users.

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.

Knack: Is Knack charged per user?

No. User accounts are unlimited on all plans. Plans are bounded by stored record count, file storage, API calls per day and automation transactions.

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.

Knack: What happens when I exceed the record limit?

You move to a higher tier or reduce stored records. Because the limit is on data rather than people, apps that accumulate history hit it while apps that track a fixed set of entities generally do not.

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.

Knack: Can I export my application or self-host it?

You can export record data. The application itself, its pages, roles, permissions and flows, is not exportable and cannot be self-hosted, so leaving means rebuilding elsewhere.

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.

Knack: Is it suitable for public-facing portals?

That is its strongest case, because logins are unlimited and role-based permissions are built in. The constraint is record volume and API throughput, not audience size.

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.

Knack: Can I use it for regulated data?

HIPAA-aligned and government cloud options exist but only on the Enterprise tier, along with private server environments. Lower tiers should not be used for regulated workloads.

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