Syncing 3 or more systems with chained syncs

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In modern enterprise architectures, data often needs to flow between multiple systems in real-time. While two-way sync between pairs of systems is powerful, organizations often need to synchronize three or more systems together. This is achieved through chained synchronization, where multiple bidirectional syncs are connected in with common tables.

For example, consider a common enterprise setup with Salesforce CRM connected to both operational databases (PostgreSQL) and analytics platforms (Snowflake). Through bidirectional sync, when a record is updated in any of these systems, the change propagates to all others. If a contact record is updated in PostgreSQL, the change syncs to Salesforce, which then syncs to Snowflake, ensuring all systems stay consistent. This transitive property of bidirectional sync means that the order of connections doesn't matter - whether Salesforce acts as the central hub connecting to PostgreSQL and Snowflake, or PostgreSQL sits in the middle connecting Salesforce and Snowflake, the end result is the same: all systems maintain perfect data consistency.

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This approach provides a clean, maintainable architecture that eliminates the need for complex many-to-many connections between systems while ensuring data remains synchronized across your entire stack.

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Use cases:

1. Alignment of CRM with Product database and data warehouse in real-time. Ensure that customer information, product usage data, and analytical insights remain consistent across all systems in real-time.
2. Data replication across cloud vendors. Chained syncs enable seamless data flow while respecting each platform's native protocols and security requirements. The data is accessible in read+write across all clouds (for instance, a postgres database available on AWS, GCP and Azure).
3. Synchronization of 3 or more services together.