DEV Community

Apache SeaTunnel
Apache SeaTunnel

Posted on

Where Does Data Flow? A Complete Guide to Apache SeaTunnel Sink Connectors (2024 Edition)

#programming #seatunnel #datascience #opensource

ai-generated-8476509\_1280

In our previous article, The Ultimate Collection of Apache SeaTunnel Source Connectors, we explored how SeaTunnel reads data. But data integration is a complete journey—reading is only the beginning. The true value comes from efficiently and reliably writing processed data into target systems. Today, we’ll focus on the “last mile” of the data journey: a deep dive into the powerful and diverse ecosystem of Apache SeaTunnel Sink connectors.

SeaTunnel’s Sink connectors are responsible for writing data streams into external storage, databases, or messaging systems. They are designed to ensure high performance, strong reliability, and transactional guarantees (including exactly-once semantics). Whether your destination is a data warehouse, a data lake, a NoSQL database, or even a simple notification tool, SeaTunnel has you covered.

sink-connectors

Let’s break the ecosystem down into nine categories to showcase the possibilities of writing data with SeaTunnel.

1. Result Backflow: Relational Databases

Writing cleaned, transformed, and computed results back into relational databases is a common business need. SeaTunnel supports high-throughput, transactional writes to these systems.

  • JDBC: A generic sink for any database with a JDBC driver.
  • MySQL / PostgreSQL / Oracle / SQLServer: Optimized sinks for mainstream databases with Upsert support.
  • Kingbase / OceanBase / DB2: Covering domestic, distributed, and traditional commercial databases.
  • Phoenix: Write data into HBase while building SQL indexes.

2. Analytics Core: Data Warehouses & OLAP

Loading data into analytical databases is key for BI reports and data insights. SeaTunnel sinks are optimized for both high-throughput batch and streaming writes.

  • ClickHouse / Doris / StarRocks: Officially recommended loading tools for new-generation MPP warehouses, offering exceptional performance.
  • Greenplum / MaxCompute / Redshift / Snowflake: Seamlessly load streaming or batch data into enterprise-grade and cloud warehouses.
  • Databend: Write data into this cloud-native warehouse.

3. Multi-Model Storage: NoSQL & Search Engines

Write data into NoSQL or search engines to meet diverse needs such as full-text search, user profiling, and graph analysis.

  • Elasticsearch / OpenSearch / Easysearch: Efficiently build search indexes.
  • MongoDB: Store document-based data.
  • HBase / Cassandra / Kudu: Columnar stores suited for massive datasets.
  • Neo4j: Insert nodes and relationships to build knowledge graphs.
  • Redis / AmazonDynamoDB: High-performance key-value stores.

4. Building the Future: Data Lakes & Lakehouses

Writing to open data lake formats is the foundation of modern, scalable data platforms. SeaTunnel offers industry-leading support here.

  • Iceberg: ACID transactions, schema evolution, hidden partitioning, and more.
  • Hudi: Copy-on-Write and Merge-on-Read table types with Upsert support.
  • Paimon: High-performance writes for streaming data lakes.

5. Data Archival: Files & Object Storage

Store data as files in file systems or cloud object storage for archiving, exchange, or as the foundation of data lakes.

  • LocalFile / HdfsFile: Write into local or HDFS file systems.
  • S3File / OssFile / CosFile / ObsFile: Full support for AWS, Alibaba, Tencent, Huawei, and more, with formats like Parquet, ORC, CSV, JSON.
  • FtpFile / SftpFile: Write files to FTP/SFTP servers.

6. Message Relay: Message Queues

Send data streams into message queues for downstream real-time applications—an essential step in building complex data pipelines.

  • Kafka / Pulsar: Send messages to distributed streaming platforms.
  • RocketMQ / RabbitMQ: Write into enterprise message queues.
  • AmazonSQS: Write into AWS SQS.

7. Real-Time Monitoring: Time-Series Databases

Write metrics, monitoring data, or IoT device data into time-series databases for real-time monitoring and alerts.

  • InfluxDB / IoTDB / TDengine: Efficient sinks for mainstream TSDBs.

8. Smart Notifications: Collaboration & Alerts

This is a particularly unique capability: pushing data results or alerts directly to collaboration tools, bridging the gap between data and people, and enabling DataOps in practice.

  • Webhook: Call any HTTP endpoint to trigger systems or send alerts.
  • Feishu / DingTalk / WeChat Work: Send data or alerts to team chats as message cards.

9. Debugging Essentials: Tools & Others

  • Console: Print data to standard output, a developer’s go-to sink for debugging.
  • Assert: Validate outputs in CI/CD pipelines; fail the job if data doesn’t match expectations.

Conclusion & Outlook

Apache SeaTunnel’s Sink ecosystem is just as impressive as its Source ecosystem. It’s more than a data mover—it’s an intelligent data distribution hub. Its core strengths include:

  1. Exactly-Once Semantics: Many connectors provide end-to-end guarantees so data is neither lost nor duplicated.
  2. High Throughput: Deep optimizations for data warehouses and lakes ensure large-scale data loads.
  3. Unified Experience: No matter the destination system, users get the same clean, simple configuration.

By combining its powerful Source and Sink ecosystems, Apache SeaTunnel has truly become the “Swiss Army knife” of data integration—flexible, efficient, and reliable for building even the most complex data pipelines.

Start your next-generation data integration journey today!

Learn more:

Top comments (0)