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Machine Learning · head to head

LlamaIndex vs VerneMQ

LlamaIndex logo

LlamaIndex

Machine Learning

Data framework for LLM applications

From
Free
Rated
-
VerneMQ logo

VerneMQ

Databases

Erlang MQTT broker whose source is Apache 2.0 but whose official binaries need a paid subscription

From
Free
Rated
-

The short version

  • Each has a real cost: LlamaIndex the free LlamaCloud plan includes 10K credits and has no pay as you go option, so work stops when credits run out; VerneMQ the official binaries and Docker images are not Apache 2.0 but sit under a EULA requiring a yearly commercial subscription, a distinction easy to miss and awkward to discover during a licence audit.
  • They diverge on capability: LlamaIndex covers Data connectors, VerneMQ covers Erlang/OTP clustering.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which LlamaIndex and VerneMQ actually diverge.

Attributes where LlamaIndex and VerneMQ differ
AttributeLlamaIndexVerneMQ
Pricing modelusage-basedquote
PlatformsLinux, Mac, WindowsLinux, Docker, macOS, Kubernetes
CategoryMachine LearningDatabases
Founded2022Unknown

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 LlamaIndex

  • Data connectors
  • Indexing
  • Query engine
  • RAG pipelines
  • Agents
  • OpenAI
  • Anthropic
  • Pinecone

Only in VerneMQ

  • Erlang/OTP clustering
  • MQTT 5.0 support
  • Plugin system
  • Backpressure handling
  • Bridge support
  • Metrics export
  • MQTT over WebSockets
  • Pluggable auth backends

What people use each for

The jobs each tool is most often brought in to do.

LlamaIndex

  • Parsing PDFs and complex documents into structured text for RAGnot VerneMQ
  • Building retrieval augmented generation pipelines over private datanot VerneMQ
  • Indexing and querying enterprise documents from an LLM applicationnot VerneMQ

VerneMQ

  • An industrial operator that wants an MQTT broker with predictable memory behaviour and no data integration features it will not usenot LlamaIndex
  • A team building from source to stay strictly under Apache 2.0 terms with no vendor licence entanglementnot LlamaIndex
  • A deployment needing custom authentication logic implemented as a plugin in Lua or over a webhooknot LlamaIndex
  • An organisation that wants a broker maintained by a small European company rather than by a vendor that keeps changing licencesnot LlamaIndex

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

LlamaIndex

  • The free LlamaCloud plan includes 10K credits and has no pay as you go option, so work stops when credits run out
  • Concurrent parse jobs are capped at 5 on Free and Starter, 20 on Pro and 100 on Enterprise
  • Pay as you go spend is capped at $500 per month on Starter and $5,000 per month on Pro
  • Enterprise SSO is Enterprise plan only
  • Volume discounts on credits and 5x higher rate limits are Enterprise only
  • SaaS or hybrid cloud deployment choice and a dedicated account manager are Enterprise only
  • Enterprise pricing is by quote with no published rate

VerneMQ

  • The official binaries and Docker images are not Apache 2.0 but sit under a EULA requiring a yearly commercial subscription, a distinction easy to miss and awkward to discover during a licence audit.
  • Octavo Labs is a very small company, so support depth, response times and the bus factor on the codebase are materially thinner than at HiveMQ or EMQ.
  • There is no data integration or rule engine layer, so routing messages into a database means writing and operating your own consumer service.
  • Operating an Erlang cluster requires runtime knowledge that most teams do not have and will use for nothing else in their stack.
  • There is no vendor-managed cloud offering, so every deployment is self-operated with the infrastructure and on-call cost that implies.

Pricing, plan by plan

LlamaIndex

Free
  • FreeFree
    • 10K monthly credits
    • Basic parsing
    • 5 concurrent jobs
  • Starter$50/month
    • 40K credits + pay-as-you-go
    • Up to 400K credits
    • 5 concurrent jobs
  • Pro$500/month
    • 400K credits + limited-time bonus
    • 20 concurrent jobs
    • Priority Slack support
  • Enterprise$null/custom
    • Custom volume discounts
    • 5x higher rate limits
    • SSO

VerneMQ

Free
  • Source buildFree
    • Apache 2.0 licensed source from GitHub
    • Full clustering and plugin capability
    • You compile and package it yourself
  • Binary packages and Docker images$undefined/year
    • Covered by the VerneMQ EULA, not Apache 2.0
    • Yearly usage subscription expected for commercial use
    • Official builds and Docker images
  • Commercial support$undefined/year
    • Evaluation, customisation and operations assistance
    • Custom development
    • Long-term maintenance agreements

Which should you pick?

Choose LlamaIndex if

  • You need data connectors.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want indexing.

Choose VerneMQ if

  • You need erlang/otp clustering.
  • You want to start without paying.
  • You work on Linux, Docker, macOS, Kubernetes.
  • You also want mqtt 5.0 support.

Questions people ask

Is LlamaIndex or VerneMQ better?
Neither clearly leads. LlamaIndex starts at Free and VerneMQ at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, LlamaIndex or VerneMQ?
LlamaIndex starts at Free and VerneMQ at Free.
Does LlamaIndex or VerneMQ run on more platforms?
LlamaIndex runs on Linux, Mac, Windows. VerneMQ runs on Linux, Docker, macOS, Kubernetes.
Can I use LlamaIndex for free?
Both have a free tier, so you can try either at no cost before committing.
What is LlamaIndex best used for?
LlamaIndex is most often used for parsing pdfs and complex documents into structured text for rag, building retrieval augmented generation pipelines over private data, indexing and querying enterprise documents from an llm application. Of those, parsing pdfs and complex documents into structured text for rag and building retrieval augmented generation pipelines over private data are not what VerneMQ is typically brought in for.
What can LlamaIndex do that VerneMQ cannot?
LlamaIndex covers Data connectors, Indexing, Query engine, RAG pipelines. VerneMQ covers Erlang/OTP clustering, MQTT 5.0 support, Plugin system, Backpressure handling.

Answered from the vendors’ own pages

LlamaIndex: How much does LlamaIndex (LlamaParse) cost?

LlamaIndex offers a Free plan with 10K monthly credits at $0/month. The Starter plan is $50/month for 40K credits plus pay-as-you-go overage up to 400K total. The Pro plan is $500/month for 400K credits. Credits are priced at 1,000 credits for $1.25.

Source
VerneMQ: Is VerneMQ free?

The source is Apache 2.0 and free. The official binary packages and Docker images are covered by a separate EULA that expects a yearly fee for commercial use.

LlamaIndex: Is LlamaIndex free?

Yes, LlamaIndex offers a free plan with 10K monthly credits, basic parsing, 5 concurrent jobs, and support for up to 100 users with no upfront payment required.

Source
VerneMQ: Is the project still maintained?

Yes. Octavo Labs AG in Zurich continues to publish 2.x releases, most recently in 2026.

LlamaIndex: What are LlamaIndex's concurrent job limits?

The Free and Starter plans allow 5 concurrent jobs. The Pro plan increases this to 20 concurrent jobs. Enterprise plans offer custom configurations with 5x higher rate limits.

Source
VerneMQ: Does it have a managed cloud?

No. Every deployment is self-hosted, with commercial support available from Octavo Labs.

VerneMQ: How does it compare to EMQX?

Narrower in features and without a rule engine, but with a simpler licence story for source builds after EMQX moved to BSL.

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