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CData Sync for Hive
 

Hive 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 Technologies

Other Drivers

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


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Replicate Apache Hive Sync Hive Logo

CData Sync provides a straightforward way to continuously pipeline your Apache Hive 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 Apache Hive to RDBMS systems to facilitate operational reporting.
  • Offload queries from operational systems to reduce load and increase performance.
  • Connect Apache Hive 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 Hive with a wide range of traditional and emerging databases including:

Amazon Redshift Amazon S3 Apache Cassandra Apache Kafka Azure Data Lake Azure Synapse Couchbase CSV Databricks Google AlloyDB Google BigQuery Google Cloud SQL Heroku / Salesforce Connect IBM DB2 Microsoft Access Microsoft Azure Tables MongoDB MySQL Oracle Database PostgreSQL SAP HANA SingleStore Snowflake SQL Server SQLite Vertica
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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 Hive Data Integration Questions

Learn more about using CData Sync to replicate Hive


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

Unlike replicating Hive 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 Hive data with SQL Server. We recommend CData Sync, an easy-to-use data pipeline tool that helps users automatically, incrementally, and continuously replicate Hive data to any database or data warehouse, including SQL Server.

Yes, CData Sync is an any-to-any data pipeline tool that supports data replication between Hive and any database or data warehouse, including NoSQL databases. The transformation capabilities of CData Sync make it easy to structure data replication jobs that automatically, incrementally, and continuously replicate Hive data to any supported NoSQL database.

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 Hive data to Amazon S3 to support backup, enable cost efficiencies, enforce security, and meet compliance requirements. CData Sync will convert Hive 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 Apache Hive data with a wide range of traditional and emerging databases.


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