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Databases · head to head

BigQuery vs SingleStore

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
SingleStore logo

SingleStore

Databases

The real-time distributed SQL database for data-intensive 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.; SingleStore high licensing costs that increase with data scale and cluster size
  • They diverge on capability: BigQuery covers Serverless compute, SingleStore covers Real-time Analytics.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and SingleStore actually diverge.

Attributes where BigQuery and SingleStore differ
AttributeBigQuerySingleStore
Pricing modelusage-basedUnknown
PlatformsWeb, Cloud APICloud (SingleStoreDB Cloud), Self-Managed
Founded20082011

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 SingleStore

  • Real-time Analytics
  • Fast Data Ingest
  • In-memory Processing
  • Distributed Architecture
  • MySQL Compatible
  • Columnar Storage
  • Vector Search
  • Kafka

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

SingleStore

  • Transaction processingnot BigQuery
  • Data storagenot BigQuery
  • Application backendnot BigQuery
  • Reportingnot BigQuery
  • Data analyticsnot 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.

SingleStore

  • High licensing costs that increase with data scale and cluster size
  • Eventual consistency in replication: secondary replicas may lag during high write loads
  • Complex operational setup requiring specialized knowledge for optimization
  • Vendor lock-in due to proprietary technology without open-source alternatives
  • Disorganized documentation and lack of online training resources

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

SingleStore

Free
  • Free Tier$0.99/month
    • Usage-based pricing
    • Limited resources

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 SingleStore if

  • You need real-time analytics.
  • You want to start without paying.
  • You work on Cloud (SingleStoreDB Cloud), Self-Managed.
  • You also want fast data ingest.
SingleStore review

Questions people ask

Is BigQuery or SingleStore better?
Neither clearly leads. BigQuery starts at Free and SingleStore at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or SingleStore?
BigQuery starts at Free and SingleStore at Free.
Does BigQuery or SingleStore run on more platforms?
BigQuery runs on Web, Cloud API. SingleStore runs on Cloud (SingleStoreDB Cloud), Self-Managed.
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 SingleStore is typically brought in for.
What can BigQuery do that SingleStore cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. SingleStore covers Real-time Analytics, Fast Data Ingest, In-memory Processing, Distributed Architecture.

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.

SingleStore: Does SingleStore offer a free tier?

Yes, SingleStore offers a free tier starting from $0.99/month with usage-based pricing. The free tier allows developers to evaluate the platform with limited resources before scaling to production workloads.

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.

SingleStore: Can SingleStore handle both transactional and analytical workloads?

Yes, SingleStore is a hybrid transactional/analytical processing (HTAP) database that combines operational (OLTP) and analytical (OLAP) workloads in a single unified engine, eliminating the need for separate systems.

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.

SingleStore: Does SingleStore integrate with Apache Spark?

Yes, SingleStore provides the Spark Connector 3.0 for bidirectional data integration with Apache Spark. The connector supports SQL, Python, Scala, Java, and R for data loading and extraction.

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.

SingleStore: Can SingleStore ingest data from Kafka?

Yes, SingleStore supports high-throughput streaming ingestion from Apache Kafka and other sources, enabling millions of events per second without requiring ETL pipelines or data movement.

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.

SingleStore: Is SingleStore available as cloud or self-managed?

SingleStore offers both deployment options: SingleStoreDB Cloud (managed service) and SingleStore Self-Managed for on-premises or private cloud deployments. The managed service handles infrastructure, scaling, and maintenance automatically.

Source
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