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Databases · head to head

BigQuery vs Turso

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
Turso logo

Turso

Databases

SQLite-lineage database platform for running very large numbers of small per-tenant databases, with an MIT-licensed engine.

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.; Turso sQLite allows one writer per database, so a single tenant's write throughput cannot be scaled horizontally and a busy tenant serialises against itself with no sharding option.
  • They diverge on capability: BigQuery covers Serverless compute, Turso covers Per-tenant databases.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Turso actually diverge.

Attributes where BigQuery and Turso differ
AttributeBigQueryTurso
Pricing modelusage-basedfreemium
PlatformsWeb, Cloud APIWeb
Founded2008Unknown

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 Turso

  • Per-tenant databases
  • MIT licence
  • Embedded replicas
  • SQLite compatibility
  • HTTP access
  • Branching
  • Point-in-time restore
  • In-process engine

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

Turso

  • Multi-tenant SaaS where each customer gets their own database for real isolation, per-tenant restore and clean deletionnot BigQuery
  • Agent or session infrastructure that creates a throwaway database per task and destroys it afterwardsnot BigQuery
  • Local-first and offline-capable applications where an embedded replica serves reads at file speed and syncs when connectivity returnsnot BigQuery
  • Embedding a SQLite-compatible engine in a product where the public domain original's closed contribution model is a problemnot 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.

Turso

  • SQLite allows one writer per database, so a single tenant's write throughput cannot be scaled horizontally and a busy tenant serialises against itself with no sharding option.
  • Per-tenant databases mean per-tenant migrations, so every schema change becomes a fan-out job that must be idempotent and resumable, and multi-database schemas, the feature meant to solve this, is deprecated.
  • There are no cross-database queries; ATTACH is deprecated on the cloud, so any report or analytic spanning tenants must be assembled in your application or in a separate warehouse you also operate.
  • Data Edge, the multi-region edge replication that was Turso's original positioning, is deprecated, so a large share of the tutorials and articles describing Turso as an edge database describe behaviour you can no longer rely on.
  • Three engine lineages share the name, SQLite, the libSQL fork and the Rust rewrite, and the Rust engine is still maturing, so SQLite compatibility needs verifying against your specific pragmas, extensions and query patterns; the cloud already restricts journal_mode and busy_timeout and makes user_version read-only.

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

Turso

Free
  • FreeFree
    • 100 databases
    • 5 GB storage
    • 500M monthly rows read
  • Developer$4.99/month
    • Unlimited databases
    • 9 GB storage
    • 2.5B monthly rows read
  • Scaler$24.92/month
    • Unlimited databases
    • 24 GB storage
    • 100B monthly rows read
  • Pro$416.58/month
    • Unlimited databases
    • 50 GB storage
    • 250B monthly rows read

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 Turso if

  • You need per-tenant databases.
  • You want to start without paying.
  • You also want mit licence.
Turso review

Questions people ask

Is BigQuery or Turso better?
Neither clearly leads. BigQuery starts at Free and Turso at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Turso?
BigQuery starts at Free and Turso at Free.
Does BigQuery or Turso run on more platforms?
BigQuery runs on Web, Cloud API. Turso runs on 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 Turso is typically brought in for.
What can BigQuery do that Turso cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Turso covers Per-tenant databases, MIT licence, Embedded replicas, SQLite compatibility.

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.

Turso: Is Turso just hosted SQLite?

Not exactly. It hosts databases built on the SQLite lineage: libSQL, an MIT fork of SQLite, and Turso Database, a newer Rust rewrite. The platform adds branching, backups, an HTTP API and programmatic database creation.

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.

Turso: Can I really run a million databases?

That is the design goal and the platform API exists to make provisioning and deletion programmatic. The practical constraints are the ones that come with it: migrations fan out, and nothing can query across databases.

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.

Turso: How do embedded replicas handle read-after-write?

Reads come from the local replica and writes go to the primary, so a read immediately after a write can return stale data unless you wait for a sync. Application code has to account for that rather than assume it.

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.

Turso: What licence is it under?

libSQL and Turso Database are both MIT. Turso Cloud is a commercial managed service built on them, so the engine is genuinely open even though the platform is not.

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.

Turso: Is Turso still an edge database?

No. Data Edge, the multi-region edge replication feature, is deprecated. The current positioning is per-tenant and embedded databases, and older material describing edge replication is out of date.

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