Graphiti vs Haystack Enterprise Platform

Graphiti is an open-source framework for building and querying temporal context graphs for AI agents. It records validity periods for facts, allowing applications to ask what is true now or what was true at a previous point in time. New structured and unstructured information is integrated incrementally rather than requiring a complete graph rebuild. Derived entities and relationships remain linked to their source episodes for provenance. Retrieval combines semantic search, keyword search, and graph traversal, with result reranking. Developers can define entity and edge types with Pydantic models or let structure emerge from incoming data. Supported graph backends listed by the project are Neo4j, FalkorDB, and Amazon Neptune; Kuzu is deprecated. Graphiti includes FastAPI REST and MCP services, supports several LLM providers, runs locally, and is self-hosted. It requires Python 3.10 or newer and an LLM API key. The Apache-2.0 framework is free.

Haystack Enterprise Platform is an operational layer for building, evaluating, deploying and governing production AI agents and applications. Teams can assemble and debug agents and retrieval-augmented generation (RAG) pipelines using a visual builder, templates, custom components and retrieval and memory settings. The Playground and Prompt Explorer support comparisons of prompts, retrieval strategies and agent workflows, as well as prototype sharing and feedback. Deployment options include deepset-managed cloud or self-hosting, with serverless autoscaling and a REST API. Governance tools include role-based access, run history, traces, performance monitoring, usage reports and guardrails. The platform lists SOC 2 Type II and ISO 27001 certifications, GDPR and HIPAA compliance, SSO, audit logs, CSA Star Level 1 and pipeline isolation. Listed model integrations include Anthropic, OpenAI, Mistral, Cohere, Gemini and custom models; data-store integrations include PostgreSQL, Snowflake, Qdrant, Weaviate and Pinecone. Pipelines can be exported as Python or YAML, and models and providers can be changed without rewriting code. Studio is free with stated limits; Enterprise pricing is custom and requires contacting deepset.