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Energy · head to head

Bidgely UtilityAI vs BigQuery

Bidgely UtilityAI logo

Bidgely UtilityAI

Energy

AI-powered energy disaggregation and customer engagement

From
On request
Rated
-
Full reviewWebsite
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

The short version

  • Only BigQuery has a free tier, so it costs nothing to try first.
  • Each has a real cost: Bidgely UtilityAI sold to utilities rather than to energy consumers, so an individual cannot buy it; 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.
  • They diverge on capability: Bidgely UtilityAI covers Energy disaggregation, BigQuery covers Serverless compute.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Bidgely UtilityAI and BigQuery actually diverge.

Attributes where Bidgely UtilityAI and BigQuery differ
AttributeBidgely UtilityAIBigQuery
Starting priceOn requestFree
Pricing modelquoteusage-based
Free tierNoYes
PlatformsWeb, Mobile, ApiWeb, Cloud API
CategoryEnergyDatabases
Founded20112008

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 Bidgely UtilityAI

  • Energy disaggregation
  • AI-powered analytics
  • Personalized recommendations
  • Customer segmentation
  • Home energy reports
  • Program enrollment
  • Mobile app platform
  • Behavioral insights

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

What people use each for

The jobs each tool is most often brought in to do.

Bidgely UtilityAI

  • Disaggregating household energy use to appliance level from meter datanot BigQuery
  • Targeting energy efficiency programmes at the right customersnot BigQuery
  • Detecting EV ownership for utility programmesnot BigQuery
  • Demand response and load flexibility planningnot BigQuery
  • Identifying customers for affordability programmesnot BigQuery

BigQuery

  • A warehouse for an organisation already on Google Cloud, where identity, logging and billing are consolidated in the same placenot Bidgely UtilityAI
  • Bursty analytical workloads with long idle periods, where paying per query beats keeping a cluster runningnot Bidgely UtilityAI
  • Event and clickstream analytics ingested continuously through the Storage Write API and queried without a load windownot Bidgely UtilityAI
  • Analytics teams with no infrastructure staff, where the absence of anything to tune or patch is worth more than dialect portabilitynot Bidgely UtilityAI

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Bidgely UtilityAI

  • Sold to utilities rather than to energy consumers, so an individual cannot buy it
  • Pricing is not published
  • Value depends on access to meter data, so it needs the utility's own data pipeline

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.

Pricing, plan by plan

Bidgely UtilityAI

On request

No published plan breakdown. See the Bidgely UtilityAI review.

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

Which should you pick?

Choose Bidgely UtilityAI if

  • You need energy disaggregation.
  • You work on Web, Mobile, Api.
  • You also want ai-powered analytics.
Bidgely UtilityAI review

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

Questions people ask

Is Bidgely UtilityAI or BigQuery better?
Neither clearly leads. Bidgely UtilityAI starts at On request and BigQuery at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Bidgely UtilityAI or BigQuery?
BigQuery has a free tier; the other does not. Paid plans start at On request for Bidgely UtilityAI and Free for BigQuery.
Does Bidgely UtilityAI or BigQuery run on more platforms?
Bidgely UtilityAI runs on Web, Mobile, Api. BigQuery runs on Web, Cloud API.
Can I use BigQuery for free?
Yes. BigQuery has a free tier, so you can try it without paying. Bidgely UtilityAI starts at On request.
What is Bidgely UtilityAI best used for?
Bidgely UtilityAI is most often used for disaggregating household energy use to appliance level from meter data, targeting energy efficiency programmes at the right customers, detecting ev ownership for utility programmes, demand response and load flexibility planning. Of those, disaggregating household energy use to appliance level from meter data and targeting energy efficiency programmes at the right customers are not what BigQuery is typically brought in for.
What can Bidgely UtilityAI do that BigQuery cannot?
Bidgely UtilityAI covers Energy disaggregation, AI-powered analytics, Personalized recommendations, Customer segmentation. BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering.

Answered from the vendors’ own pages

Bidgely UtilityAI: Why is pricing not published for Bidgely?

Bidgely does not list specific pricing on its website. Interested parties are directed to contact the company through 'Contact Us' or 'Speak with an Expert' options for pricing inquiries.

Source
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.

Bidgely UtilityAI: How do I get a pricing quote from Bidgely?

Bidgely directs potential customers to use the 'Speak with an Expert' call-to-action on their website to discuss pricing and capabilities.

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.

Bidgely UtilityAI: Is there a free trial available without a sales contact?

The website does not mention a free trial option. All pricing inquiries appear to require direct engagement with Bidgely's sales team.

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.

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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