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CData Sync for MarkLogic
 

MarkLogic ETL/ELT Data Pipeline

Automated Replication to popular Databases, Data Lakes, & Data Warehouses

  • Straightforward automated data replication.
  • Synchronize data with 100+ destinations.
  • Easy-to-use ETL/ELT data movement.

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Other Database Technologies

Other Database Drivers

MarkLogic is one of more than 200 data sources included in CData Sync [learn more].


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Replicate MarkLogic Sync MarkLogic Logo

CData Sync provides a straightforward way to continuously pipeline your MarkLogic data to any Database, Data Lake, or Data Warehouse, making it easily available to Analytics, Reporting, AI, and Machine Learning.

  • Synchronize data with a wide range of traditional and emerging databases.
  • Replicate MarkLogic to RDBMS systems to facilitate operational reporting.
  • Offload queries from operational systems to reduce load and increase performance.
  • Connect MarkLogic to analytics for BI and decision support.
  • Archive data for disaster recovery.

Automated Continuous Data Replication

CData Sync provides users with a straightforward way to synchronize data from MarkLogic with a wide range of traditional and emerging databases including:

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Key Features

Replicate Any Data Source To Any Database With a Few Clicks


  • Simple Point-And-Click Replication

    Configuring replication is easy: Login to the application, select the tables of data to replicate, and select a replication interval. Done.

  • Heterogeneous Support & Database Independence

    Supports replication across a wide range of commonly used databases, ensuring offline replication without the need to setup and maintain a new or foreign DBMS. In addition, database connectivity is extensible, providing systems integrators with the ability to synchronize with entirely new data stores.

  • Automated Iterative Data Extraction

    CData Sync extracts data iteratively, causing minimal impact on operational systems by only querying and updating data that has been added or changed since the last update.

  • Full or Partial Data Replication

    Users have complete control to define which data should be replicated and how that data should be replicated to a database. CData Sync offers the utmost in flexibility across full and partial replication scenarios.

  • Secure Backup & Archiving

    Protect your organization from the loss of valuable data. CData Sync ensures that your critical data is stored safely in the on-premise or cloud database of choice.

  • DBA-Friendly Setup

    CData Sync is completely self-contained. As a result it does not require special administration or installation on target databases.

  • Flexible Mapping, Configuring, & Scheduling

    CData Sync is incredibly simple, yet highly customizable. Almost every facet of the application can be customized to integrate with the user's ideal replication configuration.

  • Unix Cron-Style Scheduling

    CData Sync includes flexible scheduling capabilities. Users can easily schedule replication tasks at customizable intervals.

  • Dynamic Schema Replication

    Replicates schema changes dynamically, ensuring that data sources are in sync. CData Sync monitors changes in the connected datasource and the changes are automatically detected and updated within the local replicated database.

  • Advanced Logging & Transaction Monitoring

    Transaction logging is available to enable closer monitoring of changes being made to replicated data and data accessed directly through CData Sync.

  • On-Premise Or In The Cloud

    CData Sync is a go-anywhere application that is designed to perform equally well hosted on-premise (Windows, Unix / Linux, Mac OS) or in the Cloud (Azure, Amazon, Google).

Frequently Asked MarkLogic Data Integration Questions

Learn more about using CData Sync to replicate MarkLogic


MarkLogic data integration is the seamless connection and synchronization of data between MarkLogic and other organizational systems. ETL & ELT (Extract, Transform, Load / Load, Transform) processes play a crucial role in integrating MarkLogic data with other systems within an organization's data infrastructure. Data is extracted from MarkLogic, transformed as needed, and loaded into another destination, typically for storage, analysis, or reporting purposes. CData Sync plays a critical role in MarkLogic data integration, making it easy to replicate MarkLogic data any database or data warehouse and maintain parity between systems

Connecting MarkLogic to Snowflake can involve various integration methods to transfer and synchronize data between the two platforms. While it is possible to build custom integrations through APIs, the most common process involves using an enterprise-class data integration tool like CData Sync to automatically and continuously replicate MarkLogic data to Snowflake. With CData Sync, users can easily deploy robust data pipelines that create and maintain a replica of MarkLogic data to Snowflake, or any other cloud database or data warehouse.

Unlike replicating MarkLogic to a cloud data warehouse or data lake where data is commonly moved first and transformed at the destination via an ELT process, relational databases like SQL Server require ETL and in-flight data transformation. There are many ways to build ETL processes that integrate MarkLogic data with SQL Server. We recommend CData Sync, an easy-to-use data pipeline tool that helps users automatically and continuously replicate MarkLogic data to any database or data warehouse, including SQL Server.

Amazon Simple Storage Service (Amazon S3) is an object storage service providing scalability, data availability, security, and high performance. CData Sync offers the ability to create jobs that will transfer MarkLogic data to Amazon S3 to support backup, enable cost efficiencies, enforce security, and meet compliance requirements. CData Sync will convert MarkLogic data automatically into popular flat-file formats like CSV, parquet, and Avro and push those files to Amazon S3 as objects.


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Download now to setup automatic data replication of MarkLogic data with a wide range of traditional and emerging databases.


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