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Databases · head to head

BigQuery vs Domo

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
Domo logo

Domo

Business Intelligence

Business cloud for modern enterprises

From
$30000/year
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.; Domo pricing is not published; contracts start around $30,000 per year minimum, making budget planning difficult without a sales conversation
  • They diverge on capability: BigQuery covers Serverless compute, Domo covers 1000+ Connectors.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Domo actually diverge.

Attributes where BigQuery and Domo differ
AttributeBigQueryDomo
Starting priceFree$30000/year
Pricing modelusage-basedUnknown
Free tierYesNo
PlatformsWeb, Cloud APIWeb, Mobile, Api
CategoryDatabasesBusiness Intelligence
Founded20082010

Identical on both: 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 Domo

  • 1000+ Connectors
  • Real-time Data
  • Mobile BI
  • Collaboration
  • App Development
  • Salesforce
  • Google Analytics
  • Facebook

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

Domo

  • Self-service analyticsnot BigQuery
  • Data explorationnot BigQuery
  • Ad-hoc reportingnot BigQuery
  • Collaborative analysisnot BigQuery
  • Embedded analyticsnot 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.

Domo

  • Pricing is not published; contracts start around $30,000 per year minimum, making budget planning difficult without a sales conversation
  • Visualization customization is limited compared to specialized tools like Tableau, with rigid chart types and restricted pixel-level dashboard layouts
  • Version control and merge options for dataflows are very limited, making multi-developer projects prone to conflicts and overwrites
  • Workflows cannot be edited once deployed; any changes require rebuilding from scratch
  • Semantic layer lacks code-based governance, with metric definitions scattered inside individual cards rather than in a centralized governed location

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

Domo

$30000/year

No published plan breakdown. See the Domo review.

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 Domo if

  • You need 1000+ connectors.
  • You work on Web, Mobile, Api.
  • You also want real-time data.
Domo review

Questions people ask

Is BigQuery or Domo better?
Neither clearly leads. BigQuery starts at Free and Domo at $30000/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Domo?
BigQuery has a free tier; the other does not. Paid plans start at Free for BigQuery and $30000/year for Domo.
Does BigQuery or Domo run on more platforms?
BigQuery runs on Web, Cloud API. Domo runs on Web, Mobile, Api.
Can I use BigQuery for free?
Yes. BigQuery has a free tier, so you can try it without paying. Domo starts at $30000/year.
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 Domo is typically brought in for.
What can BigQuery do that Domo cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Domo covers 1000+ Connectors, Real-time Data, Mobile BI, Collaboration.

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.

Domo: Does Domo offer a free tier or trial?

Domo does not publish pricing on its website and does not offer a standard free tier. The platform uses a consumption-based credit model with minimum viable deployments starting around $30,000 per year. A free trial may be available upon request from the sales team.

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.

Domo: What data sources can Domo connect to?

Domo connects to over 1,000 pre-built connectors covering cloud applications, databases, advertising platforms, file services, spreadsheets, enterprise systems, and data warehouses. Custom integrations are possible via API.

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.

Domo: Can I self-host Domo or is it cloud-only?

Domo is a fully cloud-native, SaaS platform with no self-hosted option available. All data and applications run on Domo's cloud infrastructure.

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.

Domo: What does the credit-based pricing model mean?

Domo charges credits based on data consumption and platform activity. One credit roughly equals processing one million rows of data, though actual burn rate varies with workflows. Users purchase credit packages providing team access with unlimited user seats; only activity consumes credits, not dashboards or team size.

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.

Domo: Does Domo include AI features and what do they cost?

Domo AI features are free as part of your contract, including DomoGPT for AI chat queries. Premium AI capabilities are available through Domo AI Pro, which uses consumption-based pricing on a per-use basis.

Source
Domo: Can multiple teams collaborate on the same dashboard in Domo?

Yes, Domo supports team collaboration on shared dashboards and datasets. However, version control and merge capabilities for dataflows are limited, which can cause conflicts when multiple developers work on the same project.

Source
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