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DataX - Alibaba Open Source High-Performance Data Integration Framework

DataX is an open-source data integration tool developed by Alibaba Group, designed to handle data synchronization between various heterogeneous data sources efficiently and reliably. It provides a high-performance solution for data migration, synchronization, and ETL tasks.

Java
Added on 2025年7月3日
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DataX - Alibaba Open Source High-Performance Data Integration Framework preview
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Project Introduction

Summary

DataX is the open-source data synchronization framework from Alibaba Cloud's DataWorks, designed to facilitate data transfer and synchronization between heterogeneous data sources.

Problem Solved

Integrating data across different systems (databases, files, cloud storage) is complex, time-consuming, and often requires custom development. DataX simplifies this process by offering a unified, pluggable framework to connect and transfer data between diverse sources with high efficiency.

Core Features

Extensive Connector Support

Supports data integration between a wide range of databases, file systems, and data warehouses (e.g., RDBMS, HDFS, Hive, MaxCompute, OSS).

High Performance & Scalability

Built with a distributed architecture to achieve high throughput and performance for large-scale data transfers.

Reliability and Data Quality

Provides robust error handling, data quality checks, and transformation capabilities during the synchronization process.

Tech Stack

Java
Maven
JDBC
Plugin Architecture

Use Cases

DataX can be applied in various scenarios requiring data movement and synchronization across different systems.

Scenario 1: Database Migration

Details

Migrate data from legacy systems (e.g., on-premise databases) to cloud databases or data warehouses with minimal downtime.

User Value

Accelerate data migration projects and ensure data consistency between source and target.

Scenario 2: Data Synchronization & ETL

Details

Synchronize operational data from OLTP databases to analytical data stores for real-time reporting or batch processing.

User Value

Maintain up-to-date data in analytical systems and enable complex ETL processes across diverse sources.

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