Neo4j to Postgres Heroku integration — real-time, two-way sync

Yes. Stacksync provides a managed, real-time two-way integration between Neo4j and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Neo4j's Labels and Indexes & Constraints), map fields visually, and changes propagate both ways in milliseconds — no code required.

Change detection on Neo4j: Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties. On Postgres Heroku: Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.

On the Neo4j side: Properties, Labels, Indexes & Constraints, Databases, plus custom fields where Neo4j exposes them. On the Postgres Heroku side: Tables, Views, Materialized Views, Schemas. Stacksync auto-detects both schemas and converts types between the two systems.

Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.

Common patterns for Neo4j and Postgres Heroku: Cross-engine sync; Migration with zero-downtime cutover; Shared reference data between services. Keep the same dataset live in both Neo4j and Postgres Heroku, so each workload runs on the engine that suits it.

Neo4j: Bolt binary protocol with Cypher via official drivers, plus an HTTP query API. Authentication: Username/password (basic auth); enterprise deployments add SSO options. Postgres Heroku: SQL wire protocol (standard PostgreSQL). Authentication: Database credentials from the Heroku DATABASE_URL config var; SSL required. Stacksync manages authentication, retries, and rate limits on both sides.