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Databases · head to head

BigQuery vs Neon

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
Neon logo

Neon

Cloud

Serverless Postgres for modern developers

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.; Neon compute pricing at $0.106-$0.222/CU-hour means costs scale directly with workload, unlike fixed-price alternatives
  • They diverge on capability: BigQuery covers Serverless compute, Neon covers Serverless PostgreSQL.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Neon actually diverge.

Attributes where BigQuery and Neon differ
AttributeBigQueryNeon
Pricing modelusage-basedUnknown
PlatformsWeb, Cloud APICloud
CategoryDatabasesCloud
Founded20082021

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

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 Neon

  • Serverless PostgreSQL
  • Database Branching
  • Autoscaling
  • Bottomless Storage
  • Point-in-time Recovery
  • Connection Pooling
  • Read Replicas
  • Instant Cloning

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

Neon

  • Serverless applicationsnot BigQuery
  • Development databasesnot BigQuery
  • Preview environmentsnot BigQuery
  • Testingnot 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.

Neon

  • Compute pricing at $0.106-$0.222/CU-hour means costs scale directly with workload, unlike fixed-price alternatives
  • Separation of compute and storage may add complexity to cost prediction compared to all-in-one plans

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

Neon

Free
  • FreeFree
    • 100 CU-hours/month
    • 0.5 GB storage
    • 1 project
  • Launch$15/month
    • Pay-as-you-go compute
    • $0.35/GB storage
    • Multiple projects
  • Scale$31/month
    • Higher compute rates
    • 99.95% SLA
    • HIPAA compliance

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 Neon if

  • You need serverless postgresql.
  • You want to start without paying.
  • You work on Cloud.
  • You also want database branching.
Neon review

Questions people ask

Is BigQuery or Neon better?
Neither clearly leads. BigQuery starts at Free and Neon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Neon?
BigQuery starts at Free and Neon at Free.
Does BigQuery or Neon run on more platforms?
BigQuery runs on Web, Cloud API. Neon runs on Cloud.
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 Neon is typically brought in for.
What can BigQuery do that Neon cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Neon covers Serverless PostgreSQL, Database Branching, Autoscaling, Bottomless Storage.

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.

Neon: What is Neon and what makes it different?

Neon is a serverless PostgreSQL database that separates compute and storage, enabling automatic scaling and instant database branching. After acquisition by Databricks in May 2025, pricing has been significantly reduced.

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.

Neon: Does Neon offer a free tier?

Yes, Neon's free tier includes 100 compute units per month and 0.5 GB of storage. This is suitable for development and small projects.

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.

Neon: What are the paid plans and pricing for Neon?

Neon offers consumption-based pricing on Launch ($0.106/CU-hour, approximately $15/month) and Scale ($0.222/CU-hour, approximately $31/month) plans with separate storage billing at $0.35/GB-month. No monthly minimum required.

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.

Neon: What features does Neon provide?

Neon includes git-like branching for database copies, point-in-time recovery, data anonymization for testing, managed authentication, serverless functions, and object storage that branches with projects.

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.

Neon: What compliance and reliability guarantees does Neon provide?

Neon's Scale tier offers 99.95% uptime SLA, HIPAA compliance, SOC2 certification, and private networking via PrivateLink at no extra cost.

Source
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