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Download CData Sync v23.3.8700 for Windows + CRACK (Integrate and Replicate Data Between On-Premises and Cloud Environments)

Download CData Sync v23.3.8700 for Windows + CRACK (Integrate and Replicate Data Between On-Premises and Cloud Environments)

Version: 23.3.8700
Product Release Date: October 27, 2023
Download Cdata Sync V23.3.8700 For Windows + Crack (Integrate And Replicate Data Between On-Premises And Cloud Environments)
CData Sync is a robust and versatile data integration solution that empowers organizations to effortlessly orchestrate ETL/ELT data pipelines with speed and efficiency. Boasting a comprehensive connector library, it facilitates seamless connectivity to over 250 sources.
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CData Sync is a powerful and versatile data integration solution that empowers organizations to effortlessly build and deploy ETL/ELT data pipelines in a matter of minutes. This all-in-one tool provides seamless connectivity for integrating and replicating data across various scenarios, including on-premises to on-premises, cloud to cloud, on-premises to cloud, and vice versa.

Cdata Sync

What sets CData Sync apart is its extensive support for a wide range of sources, covering relational and NoSQL databases and popular applications such as Dynamics 365, NetSuite, Salesforce, ServiceNow, SharePoint, Workday, and many more. Additionally, it facilitates data movement to a multitude of destinations, including Snowflake, S3, Redshift, Databricks, MongoDB, SQL Server, Azure Data Lake, and more.

Efficiency is at the core of CData Sync, with fast and intelligent Change Data Capture (CDC) capabilities. By replicating only changed data from transactional databases like Oracle, SQL Server, MySQL, and Postgres, the tool reduces time and overhead, ensuring optimal data transfer.

CData Sync employs a connector-based pricing model, providing predictability and cost management in comparison to other approaches that charge per row. This approach allows organizations to scale their data replication initiatives while optimizing costs effectively.

The tool’s flexibility extends to data transformation, supporting various integration patterns and enabling the execution of ETL and ELT processes with tools like dbt Core, dbt Cloud, or custom SQL transformations. Users can schedule and monitor data pipelines, incorporating transformations, functions, and filtering as needed.

CData Sync facilitates unlimited data movement between diverse sources and destinations, bridging the gap between on-premises, public cloud (AWS, Azure, GCP), and private cloud environments. It even accommodates deployment in customer-owned environments, ensuring adherence to specific enterprise architectures and data residency requirements.

The tool caters to a spectrum of data replication use cases, from consolidating customer data for enhanced insights and reporting to seamlessly migrating databases to the cloud. Whether replicating data from Salesforce to Microsoft SQL Server or facilitating the smooth movement of CSV files to databases, CData Sync easily streamlines these processes.

The implementation of CData Sync involves straightforward steps, starting with configuring sources from a vast selection of available options. The tool automatically generates dynamic schemas and table views for all sources, ensuring a consistent process regardless of the chosen source system. Users can then effortlessly configure their destination, selecting from a cloud or on-premises options catalog, and set up data replication jobs with scheduled intervals or real-time execution.

Technical features of CData Sync include intelligent Change Data Capture, an expansive connector library, schema management, advanced data transformations, high-performance data handling, streamlined data integration, empowered business processes with events, data lineage and history with logging, business views of data, and deployment flexibility. With job scheduling and automation capabilities, CData Sync provides a comprehensive solution for efficient and reliable data integration.

Cdata Sync

CData Sync Features:

  • Intelligent Change Data Capture (CDC) and Incremental Load:
    • Efficiently captures and replicates only changed data from transactional databases (e.g., Oracle, SQL Server, MySQL, Postgres) into data warehouses.
    • Minimizes time and resource overhead by focusing on the data that has undergone modifications.
  • Expansive Connector Library:
    • Supports connectivity to a wide range of sources, including relational and NoSQL databases, as well as popular applications like Dynamics 365, NetSuite, Salesforce, ServiceNow, SharePoint, and Workday.
    • Facilitates integration with over 250 data sources, providing flexibility for diverse data ecosystems.
  • Schema Management:
    • Automatically generates dynamic schemas and table views for all sources, ensuring a consistent and straightforward process regardless of the source system.
  • Advanced Data Transformations:
    • Enables flexible execution of Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes.
    • Supports data transformations using tools like dbt Core, dbt Cloud, or custom SQL transformations.
  • High-Performance Data Handling:
    • Optimizes data transfer and replication processes for efficient and rapid movement of data between sources and destinations.
  • Streamlined Data Integration:
    • Facilitates unlimited data movement between various databases and data warehouses, including support for cloud (AWS, Azure, GCP), on-premises, and private cloud environments.
    • Eliminates boundaries, enabling seamless integration between different deployment scenarios.
  • Empowered Business Processes with Events:
    • Enhances business processes by enabling the execution of events triggered by data changes or specific conditions.
  • Data Lineage and History with Logging:
    • Provides transparency into data movement by offering detailed data lineage and historical logs.
    • Assists in tracking changes, identifying issues, and ensuring data quality and integrity.
  • Business Views of Data:
    • Offers a clear and meaningful representation of data, enhancing the usability and accessibility of integrated information for business users.
  • Deployment Flexibility:
    • Allows deployment in diverse environments, including on-premises, public cloud (AWS, Azure, GCP), and private cloud, accommodating specific enterprise architectures and data residency requirements.
  • Job Scheduling and Automation:
    • Enables users to schedule data replication jobs at desired intervals or execute them in real time.
    • Supports automation of routine tasks, improving operational efficiency.