Carbon (Perplexity) vs WhyHow: RAG Frameworks Comparison
Compare Carbon (Perplexity) and WhyHow side by side. Both are tools in the RAG Frameworks category.
The short answer
Choose Carbon (Perplexity) if pre-built connectors for easy integration with multiple data sources.
Choose WhyHow if specialized focus on knowledge graphs for RAG optimization.
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Quick Comparison
Pros & Cons: Carbon (Perplexity) vs WhyHow
- +Pre-built connectors for easy integration with multiple data sources
- +AI-optimized data processing with automatic chunking, embedding, and cleaning
- +Enterprise-grade security with SOC 2 Type II compliance and end-to-end encryption
- +Streamlined RAG development with production-ready infrastructure
- +Now backed by Perplexity AI with enhanced enterprise capabilities
- −Company was acquired and original standalone service is winding down
- −Pricing information not transparently available
- −Limited documentation on migration paths after acquisition
- −Uncertain future roadmap as integration with Perplexity progresses
- +Specialized focus on knowledge graphs for RAG optimization
- +Open-source approach with community-driven development
- +Native integration with vector databases for seamless Graph RAG
- +Supports multiple file formats including PDF, CSV, JSON, and TXT
- +Small, focused team able to move quickly and iterate
- −Very limited public information about pricing and product details
- −Small team (9 employees) may limit support and feature development
- −Relatively new company (founded 2024) with less proven track record
- −SDK and some features still in development
- −Limited enterprise adoption evidence
About Carbon (Perplexity)
Carbon is a RAG (Retrieval-Augmented Generation) framework that helps developers connect external data sources to Large Language Models. The platform provides pre-built connectors to ingest unstructured data from any source and load it into any destination, with AI-ready data processing that chunks, embeds, and cleans content for optimal LLM performance. Carbon was designed to simplify building RAG applications with features including credentials and content encryption at rest and in transit, full SOC 2 Type II compliance, and advanced data processing capabilities. In December 2024, Carbon was acquired by Perplexity AI to enhance their enterprise search capabilities, allowing users to search through files and work messages in Notion, Google Docs, Slack, and other enterprise applications.
About WhyHow
WhyHow.AI is an open-source graph tooling provider focused on RAG systems and multi-agent systems, offering a RAG-Native Knowledge Graph (KG) Platform that makes it easy to create and query performant graph structures over data. The platform has built workflows and infrastructure that natively support small graph creation specifically optimized for RAG applications, with the KG Studio Platform currently supporting PDF, CSV, JSON, and TXT file formats. WhyHow.AI is building native connectors with vector databases to enable Graph RAG capabilities from pre-existing vector chunks through an API, with an SDK coming soon for uploading pre-processed data. The platform focuses on enhancing RAG systems through knowledge graph technology, allowing for more structured and connected data representations that improve retrieval quality and context understanding in AI applications.
What is RAG Frameworks?
Frameworks and tools for building retrieval-augmented generation pipelines—document parsing, chunking, indexing, and query engines that connect LLMs to your data.
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