Building a Data Pipeline
End-to-end architecture for ingesting, processing, and storing Solana on-chain data.
A production Solana data pipeline consists of several interconnected components, each responsible for a specific part of the data flow.
Data Ingestion Layer
The entry point for all on-chain data. For real-time data, this is a gRPC/Geyser subscriber that connects to a validator node and receives a stream of account updates and transaction notifications. For historical data, this is a batch processor that fetches blocks sequentially via RPC.
Parsing and Transformation Layer
Raw blockchain data is encoded in binary formats specific to each program. The parsing layer decodes this data into structured records. For Anchor programs, the IDL provides the schema. For non-Anchor programs, you need custom parsing logic. This layer also handles data enrichment — adding derived fields like USD values, token names, and human-readable addresses.
Storage Layer
The parsed data is written to a database optimized for your query patterns. ClickHouse is recommended for analytical workloads requiring aggregations over large datasets. PostgreSQL works well for transactional queries and moderate data volumes. Redis is used for caching frequently accessed data like current token prices.
Query API Layer
Exposes the indexed data to your application through a REST or GraphQL API. This layer handles authentication, rate limiting, and query optimization.