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Databases · head to head

BigQuery vs SurrealDB

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
SurrealDB logo

SurrealDB

Databases

Multi-model database combining documents, graphs, vectors and time-series

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.; SurrealDB the listed $0.192/node/hr Scale pricing lacks transparent higher-tier rates, requiring a sales conversation for full production sizing.
  • They diverge on capability: BigQuery covers Serverless compute, SurrealDB covers Multi-model engine.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and SurrealDB actually diverge.

Attributes where BigQuery and SurrealDB differ
AttributeBigQuerySurrealDB
PlatformsWeb, Cloud APIweb, api, windows, mac, linux
Founded20082022

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 SurrealDB

  • Multi-model engine
  • ACID transactions
  • Hybrid retrieval
  • Horizontal scaling
  • Multi-region disaster recovery
  • FIPS-compliant cryptography

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

SurrealDB

  • AI agent memory and retrieval-augmented generationnot BigQuery
  • Applications needing documents, graphs and vectors in one databasenot BigQuery
  • Knowledge graph construction from unstructured datanot BigQuery
  • Regulated workloads requiring SOC2/ISO27001/HIPAA-eligible hostingnot 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.

SurrealDB

  • The listed $0.192/node/hr Scale pricing lacks transparent higher-tier rates, requiring a sales conversation for full production sizing.
  • As a newer multi-model database, it has a smaller ecosystem of drivers, ORMs and community tooling than established single-model databases.
  • HIPAA compliance is only available as an Enterprise add-on rather than included in standard paid tiers.
  • Combining multiple data models in one engine can add query-planning complexity compared to purpose-built single-model databases.

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

SurrealDB

Free
  • StartFree
    • 1 free instance, then from $0.021/hr
    • 1GB storage free forever
    • Vertical scaling to terabytes
  • Scale$0.192/month
    • $0.192/node/hr
    • Production-grade fault tolerance
    • Horizontal scaling to petabytes
  • Enterprise$undefined/month
    • Self-hosted, custom pricing
    • Clustered fault-tolerant deployments
    • FIPS-compliant cryptography

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 SurrealDB if

  • You need multi-model engine.
  • You want to start without paying.
  • You work on web, api, windows, mac, linux.
  • You also want acid transactions.
SurrealDB review

Questions people ask

Is BigQuery or SurrealDB better?
Neither clearly leads. BigQuery starts at Free and SurrealDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or SurrealDB?
BigQuery starts at Free and SurrealDB at Free.
Does BigQuery or SurrealDB run on more platforms?
BigQuery runs on Web, Cloud API. SurrealDB runs on web, api, windows, mac, linux.
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 SurrealDB is typically brought in for.
What can BigQuery do that SurrealDB cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. SurrealDB covers Multi-model engine, ACID transactions, Hybrid retrieval, Horizontal scaling.

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.

SurrealDB: What does SurrealDB cost?

SurrealDB Cloud's Start plan is free with one free instance (then from $0.021/hr), the Scale plan runs $0.192/node/hr for production workloads, and Enterprise self-hosted deployments use custom 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.

SurrealDB: Is there a free plan and what are its limits?

Yes, the Start plan includes one free instance with 1GB of storage free forever and 1GB of outbound data transfer per month, aimed at prototypes and development.

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.

SurrealDB: How is billing handled?

Customers are invoiced monthly based on actual usage in a pay-as-you-go model with no long-term commitments, though commitment-based discounts 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.

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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