Chainbase uses a dual-chain architecture designed for both speed and reliability. It separates:
1. Fast layers for indexing and computation that allow real-time queries.
2. Anchoring layers for final, auditable, and cryptographically verifiable data.
This setup enables instant access to data while ensuring a trustworthy record of events.
Data enters Chainbase through connectors that pull from RPC endpoints, mempool feeds, rollups, and archive nodes. These raw events are parsed, enriched, and structured into curated datasets, such as tokens, transfers, NFT ownership, and DeFi positions. The platform then exposes this data via REST APIs, streaming webhooks, and a SQL-like interface, letting users run complex historical queries (like combining wallet activity with off-chain data) without building pipelines themselves.
Chainbase can also sync datasets to external systems such as S3, Postgres, Snowflake, or BigQuery. This hybrid approach allows quick prototyping via APIs while supporting enterprise-scale BI workflows and avoiding vendor lock-in.
Finally, the platform is AI-ready: datasets are organized, labeled, and structured to support LLMs and agent systems, providing time-series views and feature sets that help models analyze on-chain activity and generate actionable insights. This combination of Web3 data + AI orientation sets it apart from traditional nodes or indexing services.
