Top 6 of 15 alternatives
Alternatives to LlamaIndex
Find a better fit. See what each alternative to LlamaIndex does better, where it falls short, and what it costs.
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- 01
LangChain
Open source agent frameworks plus LangSmith, a hosted platform to trace, evaluate, deploy and govern agents.
From FreeWhy it's on this listWrites code · YesThe vendor ships dcode, a free open-source terminal coding agent that writes and runs code from a prompt; it is a separate package from the paid LangSmith platform.Source ↗
Where it improves on LlamaIndex
- +Ships it · YesLangSmith Deployment runs agents in production with one-click deploy from Studio and a control-plane API; the free Developer plan shows Deployment as N/A, so shipping starts at Plus.Source ↗
- +Done-for-you service · PartlyYou run the software yourself on every self-serve plan; only Enterprise buyers get LangChain engineers, architectural guidance and team training alongside the product.Source ↗
Trade-offs against LlamaIndex
- −Bring your own key · PartlyYou can bring your own provider keys through the gateway on every plan, or buy inference as Gateway Credits, but Engine refuses your keys and bills its model use as compute units.Source ↗
- 02
LangGraph
Open-source orchestration framework and runtime for stateful, long-running LLM agents, from LangChain.
From FreeWhy it's on this listFor the reader whose real complaint is thin support for complex, production multi-agent orchestration -- the single most-cited LlamaIndex switch target in current market coverage. LangGraph is an open-source, MIT-licensed low-level orchestration framework for building stateful single-agent, multi-agent, and hierarchical workflows with human-in-the-loop controls, built-in memory across sessions, and token-by-token streaming, free to use on its own. LangSmith, LangGraph's paid platform, adds observability, evaluation, deployment, and sandboxed execution on top, separate from the free library. The tradeoff: LangGraph is deliberately low-level and expressive rather than batteries-included, so it asks more upfront design work than a framework that hides more of the orchestration logic.
Where it improves on LlamaIndex
- +Runs autonomously · YesBuilt for unattended long-running work: checkpointed durable execution lets a run survive failure and resume, and human-in-the-loop checks are described as something you add rather than a default.Source ↗
- +Open models · YesOpen-weight models run locally through the ChatOllama integration, and self-hosted vLLM and Hugging Face endpoints are documented as chat-model integrations.Source ↗
- +Model choice · YesYou choose the model. LangGraph does no model abstraction of its own and the vendor markets provider-independence; the featured integration table spans OpenAI, Anthropic, Google, Bedrock, Ollama and more.Source ↗
Trade-offs against LlamaIndex
- −Data residency · PartlyUS or EU choice inside LangChain's cloud from Plus upward; Enterprise adds hybrid and self-hosted with the data plane in your own VPC. The Developer column reads N/A.Source ↗
- 03
Mastra
Open-source TypeScript framework for building AI agents, with a hosted platform for running and observing them.
From FreeWhy it's on this listDone-for-you service · PartlyYou run the software, but Mastra sells professional services (Concierge, forward-deployed engineering) and enterprise support covering planning, prototyping and workshops.Source ↗
Where it improves on LlamaIndex
- +Runs autonomously · YesAgents iterate their own tool-use loop until a final answer or stopping condition; durable agents persist run state so a loop can outlive the request that started it.Source ↗
- +Agent permissions · YesTool approval can gate any tool call, per server or by predicate on tool name/arguments; approvals propagate up a subagent delegation chain.Source ↗
Trade-offs against LlamaIndex
- −Data residency · PartlySelf-hosted Enterprise keeps traces, prompts and outputs inside your own VPC; for the hosted platform the vendor publishes no region or jurisdiction.Source ↗
- −Certifications · PartlySOC 2 documentation is offered from the Teams plan; a DPA covering GDPR, UK GDPR and CCPA/CPRA is published, and a Vanta-hosted trust centre carries the security programme. No ISO 27001 claim found.Source ↗
- 04
Agno
Python SDK plus self-hosted AgentOS runtime and hosted control plane for building and operating agents.
From FreeWhy it's on this listWrites code · YesShips a CodingTools toolkit whose documented job is editing files and running commands in a scoped project directory.Source ↗
Where it improves on LlamaIndex
- +Done-for-you service · PartlyYou run the software yourself on every plan, but Enterprise bundles hands-on engineering help building your product agent plus monthly office hours.Source ↗
- +Runs autonomously · YesRuns execute as background jobs and on schedules without a person present; a run only pauses when it hits a tool you marked as needing approval.Source ↗
Trade-offs against LlamaIndex
- −In your pipeline · NoThe enumerated serving surfaces are REST, MCP in Claude/ChatGPT and chat apps; no pull-request or CI surface appears.Source ↗
- −Pooled budget · NoThere is no shared balance to pool because nothing inside a connection is metered; seats and connections are each priced individually and usage is unlimited.Source ↗
- −Certifications · PartlyThe enterprise page asserts SOC 2 compliance and Enterprise plans include security reviews, but no ISO 27001 or GDPR statement was found on the site.Source ↗
- 05
CrewAI
Open-source multi-agent framework with a managed platform for deploying and governing agent workflows.
From FreeWhy it's on this listFor the reader whose real complaint is setup overhead -- wanting a simpler way to stand up a working multi-agent team without assembling connectors, pipelines, and retrieval logic by hand. CrewAI is an open-source Python framework built around role-based multi-agent "crews," with a hosted enterprise platform (CrewAI Enterprise/AMP) adding a visual editor and centralized governance for platform teams, reportedly running at Fortune-500 scale. The tradeoff: CrewAI's role-based abstraction is opinionated about how agents divide work, which is less flexible than LangGraph's lower-level graph control for workflows that don't fit a "crew" shape.
Where it improves on LlamaIndex
- +Done-for-you service · PartlyYou run the software yourself, but the Enterprise plan sells forward-deployed engineers, onboarding and training separately, so people-delivered build help exists as a paid extra.Source ↗
- +Runs autonomously · YesThe vendor positions crews as autonomous workers that interact with enterprise applications unattended, with hierarchical delegation and cron scheduling available on both plans.Source ↗
- +Open models · YesLocal and open-weight serving is documented end to end, with step-by-step Ollama setup plus Hugging Face, Together, Groq and local NVIDIA NIM examples via LiteLLM.Source ↗
Trade-offs against LlamaIndex
- −How it meters · PartlyMetering is per workflow execution rather than per seat, and the free tier states its allowance, but Enterprise volumes are sized case by case with unpriced overage.Source ↗
- −Opt out of training · PartlyFramework telemetry excludes prompts and agent data by default and is disabled with one environment variable, but no page states whether platform execution data trains vendor models.Source ↗
- −Data residency · PartlyEnterprise buyers can keep execution in their own VPC or infrastructure, but no region menu is published for the managed cloud and the trust centre lists AWS in the US as cloud subprocessor.Source ↗
- 06
Letta
Stateful agent harness, cloud and SDK for agents with persistent, git-versioned memory.
From FreeWhy it's on this listWrites code · YesAgents edit and create files in your repository, including from GitHub issues and PRs.Source ↗
Where it improves on LlamaIndex
Trade-offs against LlamaIndex
- −MCP server · NoMCP runs inbound only: Letta sessions consume stdio, HTTP and SSE MCP servers; no Letta MCP server is published.Source ↗
- −Pooled budget · NoQuota attaches to each purchased Pro seat; unpaid seats get no Letta-hosted inference at all.Source ↗
- −Opt out of training · PartlyHosted messages may train future models; running your own model backend or local state means nothing is collected.Source ↗
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