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Databases · head to head

BigQuery vs DataStax

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
DataStax logo

DataStax

Databases

The real-time data company for AI applications

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.; DataStax dataStax's own Astra DB documentation states the Enterprise plan is an annual, contract-based plan with negotiated pricing, meaning list prices are not published for that tier
  • They diverge on capability: BigQuery covers Serverless compute, DataStax covers Cassandra Compatible.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and DataStax actually diverge.

Attributes where BigQuery and DataStax differ
AttributeBigQueryDataStax
Pricing modelusage-basedfreemium
PlatformsWeb, Cloud APIWeb, Aws, Azure, Gcp
Founded20082010

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

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 DataStax

  • Cassandra Compatible
  • Vector Search
  • Serverless
  • Multi-cloud
  • Streaming
  • CDC
  • GraphQL API
  • LangChain

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

DataStax

  • Real-time applicationsnot BigQuery
  • Content managementnot BigQuery
  • User profilesnot BigQuery
  • Mobile backendsnot BigQuery
  • Cachingnot 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.

DataStax

  • DataStax's own Astra DB documentation states the Enterprise plan is an annual, contract-based plan with negotiated pricing, meaning list prices are not published for that tier
  • DataStax's Astra DB documentation directs Standard plan customers to IBM's watsonx.data pricing for exact consumption-based rates following the DataStax/IBM deal, rather than publishing them on DataStax's own site

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

DataStax

Free
  • FreeFree
    • 5GB storage
    • 40M read/write ops
    • Vector search
  • Pay As You GoFree
    • Usage-based pricing
    • Multi-region
    • Enterprise support

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 DataStax if

  • You need cassandra compatible.
  • You want to start without paying.
  • You work on Web, Aws, Azure, Gcp.
  • You also want vector search.
DataStax review

Questions people ask

Is BigQuery or DataStax better?
Neither clearly leads. BigQuery starts at Free and DataStax at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or DataStax?
BigQuery starts at Free and DataStax at Free.
Does BigQuery or DataStax run on more platforms?
BigQuery runs on Web, Cloud API. DataStax runs on Web, Aws, Azure, Gcp.
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 DataStax is typically brought in for.
What can BigQuery do that DataStax cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. DataStax covers Cassandra Compatible, Vector Search, Serverless, Multi-cloud.

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.

DataStax: Is DataStax available as a managed service?

Yes, DataStax is available as Astra DB, a managed database service. Users can sign up for Astra DB directly to create accounts and access the platform.

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.

DataStax: How is DataStax priced?

DataStax (now part of IBM) does not publish pricing on its documentation homepage. Pricing information would need to be obtained through the Astra DB signup page or by contacting IBM directly.

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.

DataStax: Is there an enterprise licensing option?

DataStax is now part of IBM. Enterprise customers should contact IBM directly for licensing agreements and enterprise-specific 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.

DataStax: Can I try DataStax without an account?

To use DataStax Astra DB, account creation is required. The documentation does not mention a free trial or demonstration environment that does not require signup.

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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