Machine Learning · head to head
LlamaIndex vs Pachyderm
Pachyderm
Machine Learning
Data versioning and container pipelines that run on your Kubernetes cluster
- 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; Pachyderm it runs only on Kubernetes, so operating it means someone who can debug pods, storage classes and node pressure, and on a team without that person a cluster problem and an ML outage are the same event.
- They diverge on capability: LlamaIndex covers Data connectors, Pachyderm covers Versioned file system.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which LlamaIndex and Pachyderm actually diverge.
| Attribute | LlamaIndex | Pachyderm |
|---|---|---|
| Pricing model | usage-based | freemium |
| Platforms | Linux, Mac, Windows | Linux |
| Founded | 2022 | 2014 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).
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 Pachyderm
- Versioned file system
- Datum-based incremental processing
- Container pipelines
- Automatic provenance
- Parallel execution
- S3 gateway
- Enterprise authentication
- Object storage 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 Pachyderm
- Building retrieval augmented generation pipelines over private datanot Pachyderm
- Indexing and querying enterprise documents from an LLM applicationnot Pachyderm
Pachyderm
- Reprocessing a growing archive of images or documents where a full pass every night would be wasteful and only the new files matternot LlamaIndex
- Regulated pipelines where an auditor will ask which exact input files and which code version produced a given resultnot LlamaIndex
- Genomics and scientific workflows built from existing command line tools that are easier to containerise than to rewritenot LlamaIndex
- Teams that already run Kubernetes and want data lineage without adopting a full commercial ML platformnot 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
Pachyderm
- It runs only on Kubernetes, so operating it means someone who can debug pods, storage classes and node pressure, and on a team without that person a cluster problem and an ML outage are the same event.
- Data is held in Pachyderm's content-addressed repositories rather than as plain files in a bucket, so every other tool reaches it through the client or the S3 gateway and migrating away is a full export rather than a redirect.
- The glob pattern that decides the unit of parallel work is the most consequential line in a pipeline specification, and getting it wrong produces either one enormous serial job or millions of tiny ones whose container start-up dominates the runtime.
- Compute is billed by your cloud provider, not by Pachyderm, so a platform that looks inexpensive on the licence line runs on a cluster that has to be sized for peak pipeline load and, for training work, carries GPU nodes.
- The project's direction now sits inside a large hardware vendor's portfolio following the 2023 acquisition, and a team adopting the community edition has no contractual claim on its continued development.
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
Pachyderm
Free- CommunityFree
- Core features
- Community support
- EnterpriseFree
- Advanced security
- Premium support
- SLAs
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 Pachyderm if
- You need versioned file system.
- You want to start without paying.
- You work on Linux.
- You also want datum-based incremental processing.
Questions people ask
- Is LlamaIndex or Pachyderm better?
- Neither clearly leads. LlamaIndex starts at Free and Pachyderm at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, LlamaIndex or Pachyderm?
- LlamaIndex starts at Free and Pachyderm at Free.
- Does LlamaIndex or Pachyderm run on more platforms?
- LlamaIndex runs on Linux, Mac, Windows. Pachyderm runs on Linux.
- 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 Pachyderm is typically brought in for.
- What can LlamaIndex do that Pachyderm cannot?
- LlamaIndex covers Data connectors, Indexing, Query engine, RAG pipelines. Pachyderm covers Versioned file system, Datum-based incremental processing, Container pipelines, Automatic provenance.
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.
SourcePachyderm: Is Pachyderm open source?
The community edition is, under Apache 2.0. Authentication, role-based access control, the console and multi-tenancy sit behind an enterprise licence key, which is the set of features most organisations need once more than one team uses it.
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.
SourcePachyderm: Do I need Kubernetes to run it?
Yes. There is no non-Kubernetes deployment. A local single-node install exists for evaluation, but anything real is a cluster with object storage behind it.
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.
SourcePachyderm: How is it different from DVC?
DVC is a command line tool a person runs alongside Git, with no server. Pachyderm is a server that owns the data and schedules the work centrally. DVC records what you did; Pachyderm does it and records it.
Pachyderm: What does it actually cost to run?
The licence is separate from the infrastructure. You pay your cloud provider for the Kubernetes nodes that run every pipeline pod and for the object storage holding every version of every data set, and that bill grows with history as well as with size.
Pachyderm: Can I serve models with it?
No. It is a batch data and training pipeline system. Serving is a separate tool and a separate deployment.
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