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Evaluation of Airbyte for Data Integration in a Data Warehouse Environment
Project duration: 4 months
Brief description
The project evaluates Airbyte as a CDC tool for near-real-time replication of relational data, using a PostgreSQL database on Google GKE as an example. The goal is to assess its suitability for stable, highly available deployment in a data warehouse environment and as a cost-effective alternative to Fivetran HVR. To this end, connector configurations will be optimized, replication performance will be measured under varying data volumes using load tests, and the resource requirements of the Airbyte pods on GKE will be analyzed. Additionally, parallelization options for the replication channels are being investigated, and resilience tests (network failure, failure of the repository test database, channel termination) are being conducted to verify restart and seamless continuation from the last known state.
Supplement
The system environment consists of a GKE cluster with a Helm-based deployment of Airbyte, as well as a separate repository database serving as a test setup for production-like conditions. The source is PostgreSQL (CDC via WAL/replication slot), with the goal of creating a replicated data store to evaluate data ingestion and stability. The study examines optimal connector parameters (e.g., sync frequency, batching/buffering, checkpointing), scaling and resource allocation (CPU/RAM, pod limits/requests), the effects of varying levels of parallelism (multiple streams/channels) on throughput and node utilization, as well as behavior during failures. Controlled failure scenarios are generated to verify whether Airbyte automatically continues reading consistently, executes retries cleanly, and ensures no data gaps or duplicates occur.
Subject description
From a technical perspective, the evaluation addresses the need to provide operational data from relational source systems in a timely and reliable manner for analytics and data warehouse processes. The benefit lies in faster data availability (near real-time) for reporting, monitoring, and data-driven decisions, while simultaneously reducing dependence on proprietary solutions. Airbyte is being evaluated to determine whether it can operate CDC-based replication paths stably-even during disruptions-and whether it fits into a high-availability platform strategy. Additionally, the economic benefits are being considered: lower licensing and operating costs compared to Fivetran HVR for comparable functionality in standard replication scenarios, as well as scalable operation on Kubernetes.
IT project data
- Industries Logistics
- Specialist tasks business intelligence, data warehouse, ETL
- DP tasks Data Warehouse
- System environments Business Intelligence, Cloud Computing
- Procedure model customer standard
- Databases PostgreSQL
- Middleware and frameworks Airbyte, Cloud SQL, Google Cloud Platform (GCP), Google Cloud Storage (GCS), Google Kubernetes Engine (GKE)
Project period01.09.2025 - 31.12.2025
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