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Databases · head to head

BigQuery vs IAR Embedded Workbench

BigQuery logo

BigQuery

Databases

Google Cloud's serverless analytical warehouse, billed either by bytes scanned per query or by reserved compute slots.

From
Free
Free plan
Yes
Visit BigQueryFull review
IAR Embedded Workbench logo

IAR Embedded Workbench

Developer Tools

Complete toolchain for embedded software development

From
On request
Free plan
No
Visit IAR Embedded WorkbenchFull review

The short version

  • BigQuery starts at $6.25/mo; IAR Embedded Workbench prices on request.
  • Where IAR Embedded Workbench falls short: no pricing information published on product page; prospective customers directed to free trial or sales contact only.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

Only the attributes on which BigQuery and IAR Embedded Workbench actually diverge.

Attributes where BigQuery and IAR Embedded Workbench differ
AttributeBigQueryIAR Embedded Workbench
Starting priceFreeOn request
Pricing modelUsage-basedQuote
Free tierYesNo
PlatformsWeb, APIWeb
CategoryDatabasesDeveloper Tools

Not yet recorded: founded for IAR Embedded Workbench.

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 IAR Embedded Workbench

Nothing recorded that BigQuery does not also cover.

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

IAR Embedded Workbench

  • Embedded software development and debuggingnot BigQuery
  • Compiler and linker tools for embedded systemsnot BigQuery
  • Multi-architecture embedded development supportnot 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

IAR Embedded Workbench

  • No pricing information published on product page; prospective customers directed to free trial or sales contact only
  • Pricing model not specified; customers must request quote or try free trial to understand licensing costs
  • Embedded development tools typically require expensive licenses, but specific IAR costs unavailable online

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

IAR Embedded Workbench

On request

No published plan breakdown. See the IAR Embedded Workbench review.

Which should you pick?

Choose BigQuery if

  • You need serverless compute.
  • You want to start without paying.
  • You work on Web, API.
  • You also want separation of storage and compute.
BigQuery review

Choose IAR Embedded Workbench if

Nothing in the data separates IAR Embedded Workbench from BigQuery on the points above - pick on price and on how each one feels to use.

IAR Embedded Workbench review

Questions people ask

Is BigQuery or IAR Embedded Workbench better?
Neither clearly leads. BigQuery starts at Free and IAR Embedded Workbench at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or IAR Embedded Workbench?
BigQuery has a free tier; the other does not. Paid plans start at Free for BigQuery and On request for IAR Embedded Workbench.
Does BigQuery or IAR Embedded Workbench run on more platforms?
BigQuery runs on Web, API. IAR Embedded Workbench runs on Web.
Can I use BigQuery for free?
Yes. BigQuery has a free tier, so you can try it without paying. IAR Embedded Workbench starts at On request.
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 IAR Embedded Workbench is typically brought in for.
What can BigQuery do that IAR Embedded Workbench cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering.

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.

IAR Embedded Workbench: How much does IAR Embedded Workbench cost?

IAR Embedded Workbench pricing is not published on the product page. Prospective customers are directed to free trials or must contact the sales team to request 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.

IAR Embedded Workbench: Does IAR Embedded Workbench offer a free trial?

Free trials are available for IAR Embedded Workbench evaluation at https://www.iar.com/embedded-development-tools/free-trials, though specific trial length and limitations are not detailed on the product page.

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.

IAR Embedded Workbench: What is the pricing model for IAR Embedded Workbench?

The pricing model is not disclosed on the product page. Customers must contact the sales team to obtain quotes and understand licensing terms.

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.

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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