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Databases · head to head

BigQuery vs EMQX

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
EMQX logo

EMQX

Databases

Erlang MQTT broker for large IoT fleets, relicensed to BSL with production free use limited to one node

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.; EMQX the move to Business Source Licence 1.1 at version 5.9 in May 2025 limits free production use to a single node, so the clustering that justifies choosing EMQX now requires a paid subscription from the second node onward.
  • They diverge on capability: BigQuery covers Serverless compute, EMQX covers Erlang clustering.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which BigQuery and EMQX actually diverge.

Attributes where BigQuery and EMQX differ
AttributeBigQueryEMQX
Pricing modelusage-basedPer month by connection and session volume
PlatformsWeb, Cloud APILinux, Docker, Kubernetes, Cloud, macOS
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 EMQX

  • Erlang clustering
  • MQTT 5.0 and QUIC
  • Rule engine
  • Data integration sinks
  • Session persistence
  • Multi protocol gateways
  • Authentication and authorisation
  • Dashboard and REST API

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

EMQX

  • A connected vehicle platform needing millions of persistent MQTT sessions with QUIC for handover across mobile networksnot BigQuery
  • An industrial operator routing sensor telemetry straight into TimescaleDB or Kafka without writing a consumer servicenot BigQuery
  • An IoT product team that has outgrown a single Mosquitto instance and needs clustering and shared subscriptionsnot BigQuery
  • A smart building deployment mixing MQTT, CoAP and LwM2M devices on one brokernot 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.

EMQX

  • The move to Business Source Licence 1.1 at version 5.9 in May 2025 limits free production use to a single node, so the clustering that justifies choosing EMQX now requires a paid subscription from the second node onward.
  • The relicensing arrived in a minor release, which caught users who had pinned to 5.x expecting Apache 2.0 terms and forced legal review of existing deployments.
  • Running an Erlang/OTP cluster well requires operational knowledge most teams do not have, and diagnosing distribution, mnesia or memory issues means learning a runtime you use for nothing else.
  • Enterprise pricing is quoted rather than published for the self-managed edition, so the cost of the clustered configuration you actually need is invisible until you talk to sales.
  • The Serverless tier caps at around a thousand connections and shares infrastructure, which makes it a prototyping tier rather than a genuine small production option.

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

EMQX

Free
  • Open Source single nodeFree
    • BSL 1.1 licence since version 5.9
    • Free production use of one node only
    • All former enterprise features visible
  • ServerlessFree
    • Free monthly quota then pay as you go
    • Up to 1,000 connections
    • 8 by 5 support
  • Dedicated Flex$234/month
    • Single tenant cluster
    • Traffic allowance included
    • 24/7 support
  • Enterprise self-managed$undefined/year
    • Deploy on premises, at the edge or in any cloud
    • Clustering licensed
    • 256 MB maximum message size

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 EMQX if

  • You need erlang clustering.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Cloud, macOS.
  • You also want mqtt 5.0 and quic.
EMQX review

Questions people ask

Is BigQuery or EMQX better?
Neither clearly leads. BigQuery starts at Free and EMQX at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or EMQX?
BigQuery starts at Free and EMQX at Free.
Does BigQuery or EMQX run on more platforms?
BigQuery runs on Web, Cloud API. EMQX runs on Linux, Docker, Kubernetes, Cloud, macOS.
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 EMQX is typically brought in for.
What can BigQuery do that EMQX cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. EMQX covers Erlang clustering, MQTT 5.0 and QUIC, Rule engine, Data integration sinks.

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.

EMQX: Is EMQX still open source?

Not in the OSI sense since version 5.9. It is source-available under Business Source Licence 1.1, reverting to Apache 2.0 four years after each release.

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.

EMQX: Can I run a free cluster?

No. The additional use grant permits free production use of one node; clustering requires a commercial licence.

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.

EMQX: What changed for existing users?

Community and enterprise editions merged, so all features are now visible, but the licence terms tightened in the same minor release.

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.

EMQX: Which version is still Apache 2.0?

Releases before 5.9 remain under Apache 2.0, and each BSL release converts to Apache 2.0 four years after publication.

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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