Carbon (Perplexity) vs Pathway (2026)
Updated April 29, 2026
Overview
Carbon, acquired by Perplexity in December 2024, provided pre-built data connectors for ingesting unstructured data from 25+ sources into LLM applications. Its managed API was wound down in March 2025, with its technology now integrated into Perplexity's enterprise data connectivity stack. Carbon's connectors supported Google Drive, Notion, Slack, Confluence, and other popular data sources for RAG pipelines.
Pathway is a high-performance Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Rust engine processes millions of data points per second; uniquely mixes batch and streaming logic in the same workflow. Trusted by NATO and Intel; recently crossed 50K GitHub stars.
Key features
Core capabilities each platform advertises.
- Data connectors
- Google Drive
- Notion
- Slack integration
- Rust-powered streaming engine — millions of data points/sec
- Unified batch + streaming logic in the same workflow
- Connectors for PostgreSQL, Kafka, S3, and live APIs
- Live LLM/RAG pipelines with incremental vector DB updates
- Stateful transformations (joins, windowing, sorting) in Rust
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- 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
Cons
- 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
Pros
- Solves real-time data challenge most RAG frameworks ignore
- Rust engine genuinely fast — millions of points/sec
- Unified batch + streaming is rare and powerful
- Production references at NATO and Intel
- Pythonic API on top of Rust performance
Cons
- Streaming-first paradigm has a learning curve for batch-only teams
- Smaller community than Spark Streaming or Flink
- Best fit for real-time use cases — overkill for static RAG
- Enterprise pricing requires sales contact
What people are saying
Pathway treats your data as a continuous stream of changes rather than static snapshots, using a Rust engine known for being extremely fast and memory-efficient.
Read full reviewCarbon (Perplexity) or Pathway — which should you choose?
Choose Carbon (Perplexity) if you wantChoose if you want
Choose Pathway if you wantChoose if you want
- Real-time RAG pipelines kept in sync with live data sources
- Streaming feature pipelines for AI/ML serving
- Continuous-learning AI systems that ingest streaming events
- Real-time analytics combining batch + streaming transforms
- Mission-critical AI workloads at NATO/Intel-scale
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