LivePerson to PostgreSQL Integration

How Datrise loads LivePerson into PostgreSQL

Datrise syncs LivePerson's conversations, agents, skills, messages, surveys, and engagement metrics into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

LivePerson: Messaging-first customer conversations and bots.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How LivePerson entities map to PostgreSQL

LivePerson entity	PostgreSQL object	Notes
conversations	`liveperson_conversations`	id PK · custom fields → jsonb columns
agents	`liveperson_agents`	id PK · linked to liveperson_conversations
skills	`liveperson_skills`	id PK · linked to liveperson_conversations
messages	`liveperson_messages`	id PK · linked to liveperson_conversations

FAQ

How does Datrise handle LivePerson's custom fields in PostgreSQL?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PostgreSQL types.

How does the LivePerson to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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