Data Layer

The Data Layer is responsible for reliable ingestion, transformation, and storage of heterogeneous data sources:

  • Ingestion Connectors: High‑throughput adapters for on‑chain RPC nodes, exchange REST/WebSocket APIs, and alternative datasets (e.g., news feeds, social sentiment). Connectors implement backoff strategies, rate limiting, and schema validation.

  • Normalization & Enrichment: Streaming pipelines (e.g., Apache Kafka, Kinesis) apply schema mapping, time synchronization, and enrichment (e.g., price consolidation, indicator pre‑computations) before persisting to the time‑series database.

  • Persistence: Utilizes optimized storage engines (e.g., TimescaleDB, InfluxDB) for historical queries, and object storage (e.g., S3) for large datasets and snapshots.

  • Meta‑Data Catalog: Maintains dataset schemas, lineage metadata, and version control, enabling reproducibility and auditability.

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