Apache SeaTunnel Consulting
Build production-grade data integration pipelines with Apache SeaTunnel — real-time CDC, batch migration, and streaming ETL across 100+ connectors using the Zeta engine.
What We Build with SeaTunnel
End-to-end data integration — from log-based CDC to bulk migration and streaming ETL.
Log-based change data capture from MySQL, PostgreSQL, Oracle, SQL Server, and MongoDB — streamed to any target with exactly-once semantics.
High-throughput bulk data migration across databases, data warehouses, and data lakes with parallel readers and write batching.
Single pipeline definition for both batch and streaming workloads using SeaTunnel's Zeta engine — no separate Flink or Spark cluster needed.
Pre-built connectors for RDBMS, NoSQL, Kafka, cloud storage (S3, GCS), data lakes (Iceberg, Delta), and OLAP databases (ClickHouse, Doris, StarRocks).
Checkpoint-based recovery, automatic job restart, and exactly-once delivery guarantees via Zeta engine's distributed state management.
Pipeline metrics via REST API and Prometheus integration, Grafana dashboards, and alerting for job failures, throughput drops, and data lag.
SeaTunnel Use Cases We Deliver
Real-world data integration patterns we implement with SeaTunnel in production.
Database to Data Warehouse Sync
Stream OLTP database changes (MySQL, PostgreSQL) to ClickHouse, StarRocks, or Snowflake in real-time for analytics.
Data Lake Ingestion
Batch and incremental load from operational databases into S3, HDFS, Delta Lake, or Apache Iceberg.
Cross-Database Migration
Full schema and data migration between heterogeneous databases — Oracle to PostgreSQL, MySQL to SQL Server, and more.
Kafka → Database Sink
Consume Kafka topics and write to relational databases, Elasticsearch, or MongoDB with configurable batching and exactly-once delivery.
Multi-Source Aggregation
Merge data from multiple source databases into a single destination — unified data models for reporting and BI.
Microservice Event Streaming
Capture database events and publish to Kafka or Pulsar for downstream microservice consumption in event-driven architectures.
Connectors We Configure
SeaTunnel's 100+ connector ecosystem — we handle setup, tuning, and production hardening.
Our Pipeline Delivery Process
A structured approach from design to production-grade monitoring.
Pipeline Assessment
Review your source/target systems, data volumes, latency requirements, and connector compatibility.
Architecture Design
Design pipeline topology, parallelism, checkpoint intervals, and failure recovery strategy.
Connector Configuration
Configure source and sink connectors, CDC settings, schema mapping, and transformation logic.
Initial Load
Execute full data load with parallel readers and validate row counts and checksums.
CDC Activation
Switch to incremental CDC mode, verify lag, and validate exactly-once delivery end-to-end.
Monitoring Setup
Configure Prometheus metrics, Grafana dashboards, and PagerDuty alerts for production pipeline health.
SeaTunnel vs Other CDC Tools
When to choose SeaTunnel over Debezium, Flink CDC, or AWS DMS.
| Capability | SeaTunnel | Debezium | Flink CDC |
|---|---|---|---|
| Batch + Streaming | ✅ Unified | ❌ Streaming only | ⚠️ Streaming primary |
| Pre-built Connectors | 100+ | ~20 | ~30 |
| Operational Complexity | Low (Zeta engine) | Medium (Kafka required) | High (Flink cluster) |
| Schema Evolution | ✅ Built-in | ✅ Schema Registry | ⚠️ Manual handling |
| No-Code Config | ✅ HOCON/JSON | ⚠️ Kafka Connect JSON | ❌ Java/SQL API |
| Data Lake Support | ✅ Iceberg, Delta, Hudi | ❌ Via Kafka Sink | ✅ Via FlinkSQL |
Apache SeaTunnel FAQs
Build Your SeaTunnel Pipeline Today
Get a free pipeline assessment — we'll review your source and target systems, design the connector topology, and deliver a production-ready SeaTunnel implementation.