Product Features
Multi-Source Data Integration
The system supports data interaction and synchronization between homogeneous and heterogeneous data sources, encompassing relational databases, non-relational databases, message queues, and big data platforms. It also supports intelligent conversion of data types across heterogeneous data sources.
Multi-Scenario Data Synchronization
The system offers whole-database synchronization, multi-table synchronization, sharding synchronization, and dynamic table name synchronization for both offline and real-time scenarios. It also supports bidirectional synchronization between data sources and data marts in offline synchronization scenarios.
Intelligent Data Synchronization
During the data synchronization process, the system supports automatic mapping of database table fields, automatic table creation at the sink end, online metadata viewing and data preview, as well as automatic retry upon task failure.
Auto Schema
During real-time data synchronization, it supports intelligent recognition of dynamic schemas. There is no need to restart real-time tasks, as schema changes and associated data can be automatically synchronized to the target end.
Easy to Use
With full visualization and zero coding, it allows for field mapping configuration, data synchronization task configuration, and data cleaning and transformation. The creation of data synchronization tasks can be done through streamlined and intuitive interfaces, lowering the barriers to use and learning costs.
Unified Operations and Maintenance
It provides comprehensive monitoring capabilities for both offline and real-time tasks, offering one-stop management of data synchronization task performance. Additionally, it supports baseline alerts, operational scheduling, and more.
Features
System Capabilities
The system provides offline and real-time data synchronization capabilities, catering to various synchronization scenarios such as whole-database synchronization, multi-table synchronization, sharding synchronization, and dynamic table name synchronization. It also supports real-time synchronization of heterogeneous data from one source to multiple destinations, enabling independent management of the source and sink ends to reduce the burden on the source data.
In-Flight Data Cleansing and Transformation
The system offers in-flight data cleansing capabilities for both offline and real-time data synchronization. It supports visual configuration of data transformation functions, allowing for processing of source data during the synchronization process. Additionally, it supports offline synchronization of dirty data, primary key conflict resolution strategies, and intelligent recognition of dynamic schemas during real-time synchronization, thereby enhancing synchronization speed and data quality.
Unified Operation and Maintenance Management
The platform provides unified operation and maintenance capabilities for both offline and real-time tasks. It supports operations such as pausing, starting, and supplementing data for offline task scheduling, as well as one-click recovery for failed tasks and downstream processes. For real-time tasks, it offers capabilities such as pausing, starting, rerunning, and continuing, ensuring that data is not lost, omitted, or duplicated in abnormal situations.
Application Scenarios
Data Aggregation
Keen Dsync offers robust data synchronization capabilities for various heterogeneous data sources, supporting the aggregation of both offline and real-time data. It facilitates data integration within the data lake and data warehouse, enabling the establishment of a comprehensive enterprise data asset system. This breaks down data silos and allows data to provide more efficient value to enterprises.
Real-Time Data Warehouse Construction
By leveraging Keen Dsync's real-time synchronization capabilities, Keen Stream's real-time computing power, and Keen ADB's analytical database, enterprises can build a real-time data warehouse. This enables real-time data transformation, cleansing, merging, computing, and model layering during business operations. The results of real-time processing are then output to Keen ADB, where they are made available to applications.
Offline Full Database Migration
Offline data synchronization supports full database migration between homogeneous and heterogeneous data sources. This meets enterprises' needs for historical data migration and platform migration scenarios, allowing for rapid response to data development or query requirements across different business scenarios.
Success Cases
Conch Profiles
As a key high-tech enterprise in traditional industrial manufacturing, Conch Profiles faces issues such as poor horizontal scalability of existing systems, traditional databases unable to support massive data, unclear boundaries between cloud and edge layers, and insufficient edge data storage capacity in their digital transformation journey. Based on these challenges, they needed to build an enterprise data middle platform to construct a large-scale data-driven and data-intelligent production service system.
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AEON
AEON is a leading comprehensive retail and service enterprise group in Asia, with over 500 member companies. In recent years, as AEON's business continues to grow, the role of data in promoting business has become increasingly prominent. The group fully recognizes the importance of data platforms for business development and has initiated a data middle platform project to establish a unified data platform connecting the group's front and back-end core business systems. Through the data middle platform, business sector data is aggregated, enabling data interconnection, data standardization, and forming data assets, providing reusable data services and capabilities for business and data development teams based on technology and big data capabilities, creating a data support platform for AEON's digital transformation.
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A Petrochemical Company
The petroleum industry is a knowledge and technology-intensive industry with multiple disciplines and specialties configured, penetrated, and collaboratively researched. The main business of upstream enterprises involves oil and gas exploration, oil and gas field development, drilling engineering, downhole operations, surface construction, material management, business management, water and electricity, communications, medical and health, and more. Information technology in the petroleum industry has consistently accompanied the development of petroleum enterprises and played a huge role. Petroleum industry data has several significant characteristics: extremely dispersed data distribution, massive data volume, complex data structure, high data utilization value, multiple storage media, complex formats, and complex software usage environments...
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