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DataWorks:More scenarios and practices

Last Updated:Jun 08, 2026

Step-by-step tutorials for specific data source and target combinations in DataWorks Data Integration, covering batch sync, real-time CDC, JSON migration, and IoT data ingestion.

Each tutorial covers a specific source-to-destination combination and walks you through configuration, execution, and verification. For higher-level planning and architecture guidance, see [Common business scenarios]().

Choose a sync method

Before picking a tutorial, identify your sync requirements:

Requirement

Recommended method

Typical use case

One-time or scheduled full copy

Batch sync node

Historical data migration, periodic snapshots

Low-latency change tracking from relational databases

Real-time CDC sync

MySQL or Oracle to MaxCompute with near-real-time updates

Serverless, no resource group to manage

Serverless sync task

Ad hoc or lightweight pipelines without dedicated resources

Semi-structured source (JSON files in OSS)

Batch sync with JSON reader

Log files, event data stored as JSON in OSS

Device telemetry at scale

IoT data ingestion pipeline

Time-series sensor data from IoT Platform

If you are unsure which method fits your workload, consider these factors:

  • Latency: CDC sync delivers changes within seconds. Batch sync runs on a schedule (minutes to hours).

  • Source type: CDC requires a relational database with binary logging or change tracking enabled. Batch sync supports a broader range of sources.

  • Infrastructure: Batch sync and real-time sync require a dedicated resource group. Serverless sync tasks do not.

Available tutorials

Sync from relational databases

  • MySQL to MaxCompute (real-time CDC) — Sync incremental changes from MySQL using change data capture. Covers enabling binlog, configuring the CDC reader, and verifying row-level changes in MaxCompute.

  • MySQL to MaxCompute (batch) — Schedule a full or incremental batch sync from MySQL. Covers watermark-based incremental extraction and partition writing in MaxCompute.

  • Oracle to MaxCompute — Migrate Oracle tables to MaxCompute with type mapping and partition configuration.

Sync from document and object stores

  • OSS JSON files to MaxCompute — Parse and load semi-structured JSON files from OSS into MaxCompute tables. Covers schema mapping, nested field flattening, and handling malformed records.

  • MongoDB to MaxCompute (batch read) — Extract documents from MongoDB collections and write to MaxCompute. Covers collection filtering, field projection, and write mode configuration.

IoT and streaming ingestion

  • IoT Platform to MaxCompute — Ingest time-series device telemetry from Alibaba Cloud IoT Platform into MaxCompute. Covers topic subscription, timestamp parsing, and partition-by-time configuration.

  • [Common business scenarios]() — Architecture patterns and scenario overviews for planning your integration strategy.

  • [Data Integration overview]() — Supported connectors, resource group requirements, and sync node types.

  • [Configure a batch sync node]() — Reference for all reader and writer plugin parameters.

  • [Configure a real-time sync node]() — Reference for CDC source configuration and exactly-once delivery settings.