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Databases · head to head

BigQuery vs SAS

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
SAS logo

SAS

Machine Learning

Analytics, AI and data management software

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.; SAS sAS publishes no rate, no minimum and no named cost driver; the how to buy page offers only a customized price quote based on your requirements and deployment preferences
  • They diverge on capability: BigQuery covers Serverless compute, SAS covers Statistical analysis.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and SAS actually diverge.

Attributes where BigQuery and SAS differ
AttributeBigQuerySAS
Pricing modelusage-basedsubscription
PlatformsWeb, Cloud APILinux, Windows, Web
CategoryDatabasesMachine Learning
Founded20081976

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 SAS

  • Statistical analysis
  • Machine learning
  • Forecasting
  • Text analytics
  • Optimization
  • Python
  • R
  • Hadoop

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

SAS

  • Regulated statistical analysis and clinical reportingnot BigQuery
  • Enterprise data management, visualization and decisioning on one licensed platformnot 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.

SAS

  • SAS publishes no rate, no minimum and no named cost driver; the how to buy page offers only a customized price quote based on your requirements and deployment preferences
  • Most new and existing customers are routed through authorized resellers rather than buying direct
  • Cloud marketplace purchases require choosing between pay as you go and bring your own licence, each with different licensing terms

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

SAS

Free
  • SAS OnDemand for AcademicsFree
    • Academic use
    • Core SAS
  • SAS ViyaFree
    • Full platform
    • Cloud-native
    • AI/ML

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 SAS if

  • You need statistical analysis.
  • You want to start without paying.
  • You work on Linux, Windows, Web.
  • You also want machine learning.
SAS review

Questions people ask

Is BigQuery or SAS better?
Neither clearly leads. BigQuery starts at Free and SAS at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or SAS?
BigQuery starts at Free and SAS at Free.
Does BigQuery or SAS run on more platforms?
BigQuery runs on Web, Cloud API. SAS runs on Linux, Windows, Web.
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 SAS is typically brought in for.
What can BigQuery do that SAS cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. SAS covers Statistical analysis, Machine learning, Forecasting, Text analytics.

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.

SAS: Does SAS offer a free trial?

Yes, SAS offers a free trial through a private trial environment for SAS Viya. Interested customers can request access by submitting a trial form on their website.

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.

SAS: How does SAS price its software?

SAS does not publish standard pricing on its website. Instead, it uses a custom enterprise sales model where customers can choose between paying as-you-go or purchasing SAS Viya Enterprise. Specific pricing must be requested directly from their 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.

SAS: What are my pricing options?

SAS offers flexible purchasing models including pay-as-you-go and enterprise licensing options. The company states they can help you find the environment that fits your needs, but specific terms must be discussed with sales.

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.

SAS: How do I get a pricing quote?

You can request pricing through their website by using the quote request form, requesting a customized demo, or contacting their sales team directly.

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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