Edge-First, Brokerless: The Case for Log-Native Databases in Edge AI

Edge-scale real-time syncing just found its heart: a log-native database with no brokers. UnisonDB makes the log itself the database, so replication, streaming, and durability share one mechanism ^[1].

Writes are WAL-first, stored durably, and streamed instantly—no separate CDC or Kafka ^[1].

It’s built in Go and uses a B+Tree storage engine on top of a streaming WAL, so edge nodes can read locally while syncing upstream ^[1].

No external brokers, no double-pipeline—just a single source of truth that streams ^[1].

Out-of-the-box deployment topologies include: - Hub-and-Spoke — central hub fans data out to 100+ edge nodes ^[1] - Peer-to-Peer — regional datacenters replicate changes between each other ^[1] - Follower/Relay — read-only replicas tail logs for analytics or caching ^[1]

Each node maintains its own offset in the WAL, so replicas can catch up from any position without re-syncing the entire dataset ^[1].

UnisonDB’s goal is to make log-native databases practical for both core and edge—combining replication, storage, and event propagation in one Go-based system ^[1].

"I vibe coded a database engine from scratch" ^[2].

The conversations around edge databases aren’t just about features; they’re about where consistency, replication, and deployment belong—in the log, at the edge, with brokerless clarity ^[1]. Watch how these ideas evolve as edge-scale realities mature ^[2].

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