airbyte

Design Airbyte ELT pipelines with sync modes, cursors, and dbt normalization.

14|1|Updated May 5, 2026
One-click install
npx skills add https://github.com/ivanshamaev/de-agent-skills --skill airbyte
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: airbyte
Source: https://github.com/ivanshamaev/de-agent-skills/tree/main/skills/airbyte
Command: npx skills add https://github.com/ivanshamaev/de-agent-skills --skill airbyte

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Airbyte ELT helps teams reliably move data from sources to destinations while supporting full refresh and incremental syncing, including deduped incremental upserts and schema evolution handling.

Core Features & Use Cases

  • Connection, stream, and catalog design: Configure sources, destinations, connections, streams, and sync schedules using Airbyte’s catalog metadata.
  • Sync mode coverage: Apply Full Refresh Overwrite/Append and Incremental Append/Append+Deduped with cursor fields and primary keys.
  • Raw-to-normalized workflow: Land raw records into _airbyte_raw_ / meta-enriched structures and optionally perform dbt-based basic normalization for typed tables.
  • Operational automation: Manage connections via Airbyte REST API or Terraform and orchestrate syncs from Apache Airflow.
  • Schema evolution & monitoring: Use non-breaking schema update policies, understand breaking change behavior, and monitor sync health through UI logs and metrics.

Quick Start

Use the airbyte skill to design an Airbyte pipeline that syncs a PostgreSQL “orders” source into Snowflake using Incremental Append + Deduped with updated_at as the cursor and order_id as the primary key.

Frequently Asked Questions about airbyte

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I configure an Airbyte incremental sync with deduped upserts from PostgreSQL to Snowflake?

To configure an Airbyte incremental sync, select Incremental Append + Deduped mode, specify cursor fields like `updated_at` and primary keys like `order_id` for per-stream policies to capture changes and deduplicate records in the analytical destination.

What is the difference between Airbyte full refresh and incremental append sync modes?

Airbyte full refresh overwrites or appends entire snapshot data per sync, whereas incremental append captures only new records using stateful cursors, and incremental append + deduped merges them using primary keys to maintain a current dataset view.

Can I manage Airbyte connections using Terraform and orchestrate syncs with Airflow?

Yes, you can manage Airbyte connections via the REST API or Terraform for infrastructure-as-code automation, and orchestrate the resulting ELt sync schedules directly from Apache Airflow for production pipeline execution.

How does Airbyte handle schema evolution during ELT pipelines?

Airbyte handles schema evolution using non-breaking schema update policies to automatically adapt to new columns, while clearly defining breaking change behaviors to prevent pipeline failures when source structures unexpectedly shift.

What are the deployment options for running Airbyte ELT pipelines in production?

Airbyte ELT pipelines can be deployed in production using abctl for local management, Helm for Kubernetes environments, or Airbyte Cloud, enabling sync health monitoring and alerting readiness through UI logs and metrics.

Do I need to specify primary keys and cursor fields for every stream in an Airbyte connection?

Yes, to use Incremental Append + Deduped sync modes, you must specify cursor fields for change capture and primary keys for deduplication on a per-stream basis within the Airbyte connection catalog metadata.