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Databases · head to head

BigQuery vs ScyllaDB

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
ScyllaDB logo

ScyllaDB

Databases

The real-time big data database compatible with Cassandra

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.; ScyllaDB enterprise tier requires custom quote from sales
  • They diverge on capability: BigQuery covers Serverless compute, ScyllaDB covers Cassandra Compatible.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and ScyllaDB actually diverge.

Attributes where BigQuery and ScyllaDB differ
AttributeBigQueryScyllaDB
PlatformsWeb, Cloud APILinux, Docker, Kubernetes, Web
Founded20082015

Identical on both: starting price (Free), pricing model (usage-based), 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 ScyllaDB

  • Cassandra Compatible
  • DynamoDB Compatible
  • 10x Throughput
  • Low Latency
  • Auto-tuning
  • Lightweight Transactions
  • Change Data Capture
  • Cassandra Drivers

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

ScyllaDB

  • 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.

ScyllaDB

  • Enterprise tier requires custom quote from sales
  • Pricing varies by cloud provider, storage, and instance configuration
  • Contracts available but commitment required for subscription discounts

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

ScyllaDB

Free
  • ScyllaDB Cloud Standard$null/variable
    • Usage-based billing: vCPU, RAM, NVMe SSD storage
    • 2-hour P1 support response time
    • 99.9% uptime SLA
  • ScyllaDB Cloud Professional$null/variable
    • Enterprise-grade scalability
    • 1-hour P1 support response
    • Enhanced features included
  • ScyllaDB Cloud Premium$null/variable
    • Custom security and networking
    • 15-minute P1 support response
    • 99.99% uptime SLA
  • ScyllaDB Enterprise$null/quote
    • Self-managed deployment
    • On-premise or private cloud
    • Custom quote required

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 ScyllaDB if

  • You need cassandra compatible.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Web.
  • You also want dynamodb compatible.
ScyllaDB review

Questions people ask

Is BigQuery or ScyllaDB better?
Neither clearly leads. BigQuery starts at Free and ScyllaDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or ScyllaDB?
BigQuery starts at Free and ScyllaDB at Free.
Does BigQuery or ScyllaDB run on more platforms?
BigQuery runs on Web, Cloud API. ScyllaDB runs on Linux, Docker, Kubernetes, 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 ScyllaDB is typically brought in for.
What can BigQuery do that ScyllaDB cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. ScyllaDB covers Cassandra Compatible, DynamoDB Compatible, 10x Throughput, Low Latency.

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.

ScyllaDB: How is ScyllaDB Cloud pricing calculated?

ScyllaDB Cloud uses transparent, resource-based billing based on instance type (vCPU and RAM), NVMe SSD storage, service plan tier, deployment model, and cloud provider costs.

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.

ScyllaDB: Does ScyllaDB offer a free trial?

ScyllaDB offers a 30-day developer trial on smaller instances and a 48-hour production evaluation trial with full-grade instances.

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.

ScyllaDB: What cost savings are available for long-term ScyllaDB commitments?

ScyllaDB subscription contracts provide up to 70% or more in savings compared to on-demand hourly billing. 1-year and 3-year contract options are available.

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.

ScyllaDB: How much cheaper is ScyllaDB than DynamoDB?

Unlike DynamoDB which charges per read/write unit, ScyllaDB charges based on resource usage only, potentially delivering 50% or greater cost reduction for high-throughput workloads.

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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