Used BigDataPumper for Oracle and NoSQL for Windows?


Editors’ Review

Download.com staff
BigDataPumper offers high-performance data migration between Oracle and various NoSQL databases. Its GUI wizard simplifies transfers, supports custom transformations, and handles all major data types.
  • Pros

    • High-performance data migration
    • Supports Oracle and multiple NoSQL databases
    • User-friendly GUI wizard
    • On-the-fly custom data transformations
    • Parallel data transfer up to 20 degrees
  • Cons

    • Specific NoSQL databases are not listed
    • No mention of error handling or reporting
    • Limited visual feedback on migration progress
    • No built-in data validation features

Used BigDataPumper for Oracle and NoSQL for Windows?


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Full Specifications

GENERAL
Release
Latest update
Version
2.0.72
OPERATING SYSTEMS
Platform
Windows
Operating System
  • Windows 8
  • Windows XP
  • Windows Server
  • Windows NT
  • Windows 98
  • Windows ME
  • Windows Vista
  • Windows 2000
  • Windows 2003
  • Windows 7
  • Windows 10
Additional Requirements
None
POPULARITY
Total Downloads
340
Downloads Last Week
0

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Developer’s Description

Perform data migration between Oracle and NoSQL databases as MongoDB, Cassandra.
BigDataPumper is an innovative, powerful and convenient product which is a part of spViewer Software BigData migration suite. It provides high-performance data migration functionality between any of the following supported databases: Oracle, MongoDB, Couchbase, Apache Cassandra, CouchDB, HBase. With BigDataPumper GUI wizard you can easily perform data transfer between supported databases in any direction. You can create your custom data transformations on the fly and import several custom data sources (based on your custom complex filter conditions) to target Oracle or NoSQL database in parallel. All main Oracle and NoSQL data types (including XML, CLOB and BLOB) are supported for data transfer between databases. You are able also to view and manage database data and export it to a readable JSON file format. The data transfer process can be parallelized up to 20 degrees providing a very high migration performance of big amounts of data.

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