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Databases · head to head

BigQuery vs ChartMogul

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
ChartMogul logo

ChartMogul

Business Intelligence

Subscription analytics platform

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.; ChartMogul the free tier stops at $10K MRR, so it lapses precisely as a company starts to matter
  • They diverge on capability: BigQuery covers Serverless compute, ChartMogul covers MRR Analytics.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and ChartMogul actually diverge.

Attributes where BigQuery and ChartMogul differ
AttributeBigQueryChartMogul
Pricing modelusage-basedsubscription
PlatformsWeb, Cloud APIWeb, Api
CategoryDatabasesBusiness Intelligence
Founded20082014

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 ChartMogul

  • MRR Analytics
  • Churn Analysis
  • Cohort Analysis
  • Customer Segmentation
  • Revenue Recognition
  • Stripe
  • Chargebee
  • Recurly

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

ChartMogul

  • MRR trackingnot BigQuery
  • Churn analysisnot BigQuery
  • Revenue analyticsnot BigQuery
  • Subscription metricsnot BigQuery
  • Financial forecastingnot 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.

ChartMogul

  • The free tier stops at $10K MRR, so it lapses precisely as a company starts to matter
  • Starter is capped at 3 team members and a single billing system connection
  • Two-way CRM sync and warehouse integration require the Pro tier
  • Pricing scales with your ARR rather than with usage, so the bill rises as the business grows
  • Enterprise starts at $19,900 a year and is required above $10M ARR

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

ChartMogul

Free
  • FreeFree
    • Up to $120K ARR tracked
    • 1 billing source
    • Unlimited team members
  • Starter$59/month
    • $59-$707/month based on ARR
    • Up to $10M ARR tracked
    • 1 billing source
  • Pro$99/month
    • $99-$1,199/month based on ARR
    • Up to $10M ARR tracked
    • 5 billing sources
  • Enterprise$19900/year
    • Custom pricing available
    • Unlimited ARR tracked
    • 15 billing sources

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 ChartMogul if

  • You need mrr analytics.
  • You want to start without paying.
  • You work on Web, Api.
  • You also want churn analysis.
ChartMogul review

Questions people ask

Is BigQuery or ChartMogul better?
Neither clearly leads. BigQuery starts at Free and ChartMogul at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or ChartMogul?
BigQuery starts at Free and ChartMogul at Free.
Does BigQuery or ChartMogul run on more platforms?
BigQuery runs on Web, Cloud API. ChartMogul runs on Web, Api.
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 ChartMogul is typically brought in for.
What can BigQuery do that ChartMogul cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. ChartMogul covers MRR Analytics, Churn Analysis, Cohort Analysis, Customer Segmentation.

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.

ChartMogul: How much does ChartMogul cost for a small SaaS startup?

ChartMogul offers a free plan for companies with up to $120K ARR. Starter plans begin at $59 per month for smaller ARR amounts and scale up to $707 per month, with a 17% discount available for annual commitments. Source: https://chartmogul.com/pricing

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.

ChartMogul: What are the team member limits on ChartMogul plans?

The Free and Pro plans include unlimited team members, while the Starter plan is limited to 3 team members. Enterprise plans offer unlimited users with custom pricing. Source: https://chartmogul.com/pricing

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.

ChartMogul: How many billing sources can each ChartMogul plan integrate?

Free and Starter plans support 1 billing source each. Pro plans increase to 5 billing sources. Enterprise plans support 15 billing sources with custom pricing and unlimited integration capabilities. Source: https://chartmogul.com/pricing

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.

ChartMogul: Does ChartMogul offer an annual payment discount?

Yes, ChartMogul provides a 17% discount when paying annually instead of monthly on Starter and Pro plans. Enterprise customers can discuss custom annual pricing with the sales team. Source: https://chartmogul.com/pricing

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.

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