Database Clustering - Replication Solves Real-Time Data Access Requirements

Database clustering involves database replication to achieve high availability (mirroring, redundancy and disaster recovery), workload balancing for performance or scaling (queries, reporting, business intelligence, analytics and data warehousing), maintenance (upgrades, migration, testing and development), database consolidation and other objectives for data access, efficiency and better decision making. It is use database clustering and replication services where the source and target databases are at different version levels and even different types of databases all together, such as PostgreSQl to Oracle replication, or DB2 to SQL. Database clustering can be implemented for a mix of on premise, virtual and cloud environments, using any of the following replication scenarios for various objectives:

• from one database source to one target database (one way)
• from one database source to multiple target databases (distributed)
• from multiple database sources to one target database (consolidated)
• from one database source to one or more target database cascaded to one or more targets again (cascaded)
• one or more database sources to one or more target database (bi-directional)
• one source database to two different databases or even a hybrid combination of any of these scenarios (hybrid)

Most database clustering solutions cannot meet complex business requirements when disparate platforms are a part of the equation or if complicated and long distance replication scenarios exist. Businesses with unique or complicated plans for database clustering should check out the advanced Database Replication software for clustering, with built-in conflict resolution and collision monitoring. It allows companies to replicate in real-time and transform data to and from the following databases: Microsoft SQL Server, Microsoft Azure SQL, IBM DB2, Oracle, Oracle RAC, MySQL, PostgreSQL, Teradata, IBM Informix and Sybase, of which the source and targets can be different combinations. Removing these technical barriers is key to real-time data sharing, which do not require abandoning existing investments and spending a lot of time and money on integration.

Today’s business demands, mergers, acquisitions and tougher regulations are driving the needs for access to data in real-time. Advanced database replication abilities address these requirements, enabling companies to effortlessly replicate data from virtually any database to almost any other database, without large integration costs. Regardless of the purpose or reason, the advanced Database Replication software can replicate data between both homogeneous or heterogeneous databases, including if using different database management systems, running on different hardware and operating system platforms, and using different database schemas. The database replication software can keep entire databases in sync or specified portions.

The intuitive database GUI manager provides pre-defined templates for each database type to make replication setup quick and simple, but allows users to edit schema using Java-like controls for customization. The GUI makes it easy to map between the field names and data structures on the different databases, without risk of inaccurate data being populated onto new database. The GUI wizard for replication and customization removes all complexity, including not needing custom scripts, programming, indexing, rationalization, and will create target database tables automatically.

A quick and simple means to reduce administration, replace manual processes, and immediately automate database replication between databases, operating systems and physical, virtual or cloud environments. Real-time database replication allows companies to share data to improve business efficiency and decision making by keeping databases in sync, enabling access to information when, where and how it is needed for queries, reports, business intelligence, data warehousing and more.

“The one word that best describes the state of analytic data in large organizations is “fragmented.” Despite their best intentions, CIOs are struggling to deliver consistent data that provides a single view across the enterprise.” TDWI