uplyst.
PostgreSQL integration
Bring PostgreSQL application data into Uplyst to connect orders, customers and inventory with the systems around them.
PostgreSQL connection optionsInitial records and subsequent changes share a consistent starting point.
- SnapshotExisting recordsA consistent view of the selected tables.
- Logical decodingCommitted changesInserts, updates and deletes from the write-ahead log.
- UplystConnected entitiesOrders, customers and inventory linked to their wider business context.
Connect application records to the wider business
PostgreSQL tables and views can supply approved records to Uplyst's intelligence layer. Shared identifiers connect those records with customer, finance and supply chain information, so an order can be understood alongside its payment, fulfilment and stock position.
Scheduled reads suit reference data and periodic analysis. For more frequent changes, PostgreSQL logical decoding exposes committed changes from the write-ahead log. An initial snapshot and a corresponding log position provide a consistent starting point. The access method depends on the database configuration and the required freshness.
Scoped access and log retention
Logical replication requires replication privileges and the appropriate server configuration; the initial table copy also requires read access. Selected tables, secure connections and a dedicated integration identity keep access aligned with the data needed by the business.
Replication slots retain information needed by their consumers. Monitoring consumer progress and retained WAL helps protect source capacity when processing slows or stops.
Keep updates attached to the correct record
Primary keys and replica identity determine how PostgreSQL identifies updated or deleted rows. Combined with the source database and table, those keys provide an unambiguous link to the business entity in Uplyst.
Order headers, line items and inventory movements may change within the same transaction. Retaining those relationships supports a coherent view of the order and the stock it affects.
| Capture detail | Why it matters |
|---|---|
| Source table and primary key | Deterministic record identity |
| Transaction boundary | Consistent related changes |
| Log sequence position | Restart and diagnostic reference |
| Delete information | Removal or tombstone handling |
Order transaction history
Database orders_uk · SO-7842 · London fulfilment
Transaction 84231
| Source table | Record identity | Committed change |
|---|---|---|
UPDATEpublic.orders | SO-7842Order header | ReleasedPrevious state: Confirmed |
UPDATEpublic.order_lines | SO-7842 / 10Item VAL-204 | 24 units allocatedOrder line 10 |
INSERTpublic.stock_reservations | RSV-9021SO-7842 / 10 · LDN-01 | 24 units reservedItem VAL-204 · each |
Decoded commit position
0/16B6A20Applied context position
0/16B6A20All three row changes applied together
Database, table and primary key identify each record. The log position identifies progress through the transaction history.
Keep business records current.
Recover without duplicating business actions
After an interruption, logical decoding can deliver recent changes again. Stable record keys and durable processing checkpoints allow those changes to be applied consistently. Any resulting workflow also needs to recognise repeated events before taking an external action.
Know when operational data is current
Source lag, applied log position and reconciliation results show whether an order or stock view reflects current database activity. Schema changes, deleted records and interruptions need to remain visible to the team responsible for the connection. If retained history is no longer available, a fresh snapshot and reconciliation can restore a complete view.
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