Gallery Case Study

SoundHub Artist Analytics

A music artist analytics platform that aggregates metrics from Spotify, YouTube, JioSaavn, Apple Music and Wynk into one time-series store.

Side ProjectOngoing
SoundHub Artist Analytics
Platforms5
StorageTime-series
RetriesIdempotent

Problem

In the Indian music market no single analytics source covers every platform, and polling many rate-limited upstream APIs risks bursts, duplicates and gaps.

Solution

  • Designed a BullMQ ingestion pipeline with backpressure on rate-limited upstream polling.
  • Used jittered scheduling to prevent thundering-herd bursts, and idempotent jobs so retries never double-write metrics.
  • Modelled ingestion on TimescaleDB hypertables with continuous aggregates for rollups.

Technical Highlights

  • UUIDv7 internal keys for index locality.
  • Prefixed NanoIDs for public identifiers.
  • One store for cross-platform artist trends.

Outcome

A single, consistent view of an artist's performance across platforms, built on an ingestion pipeline that is safe to retry.

NestJSPostgreSQLTimescaleDBRedisBullMQNext.js