Synchronized Data Integration for Hybrid Cloud

Transcription

1 Synchronized Data Integration for Hybrid Cloud Flexible. Hyper-connected. Policy-based.

2 New digital business demands on enterprise data Privacy Security Synchronize Real-Time Analytics Enterprise Data Synchronize Edge Computing Synchronize Hybrid Cloud Operations Private Public SaaS Traditional

3 The impact of hybrid cloud on enterprise data 83% 59% Enterprise Workloads will be in the Cloud by Need data synchronization between cloud & on-premise 2 77% Data Integration is Critical for Cloud 2 Top 3 cloud concerns Data Security & Regulations Data Portability Cloud Lock-in 3 1 Logic Monitor Cloud Vision 2020 Future of Cloud Survey 2 Oracle IOUG Data Integration Survey 3 Bain & Company Changing Face of the Cloud CIO Survey 3

4 Choice of topologies Easily deploy a variety of topologies in minutes Modify topologies during runtime without service interruption and add new sources or destinations dynamically High-availability and scalability options are available to easily customize out-of-box with advanced features On-Premise On-Premise Migration Public Cloud Innovation Public Cloud Analytics On-Premise Public Cloud Operational Integration On-Premise Public Cloud

5 Continuous synchronization between different database types Choose one or more destination database types appropriate for the use case Automatically create initial database copy and then synchronize each subsequent transaction without manual intervention or user tracking of transaction numbers or logs Dynamically add sources and destinations without service interruption On-Premise Public Cloud Aurora, Oracle, or MySQL

6 Policy-based custom data synchronization Selectively filter, mask/encrypt, or transform data at the schema, table, row, or column level without impacting the source data Enhance privacy by selectively encrypting or masking private data Facilitate data reengineering by selectively transforming data Customize data at the source or destination according to the needs of the use case, such as reducing network traffic or preserving privacy

7 Griddable.io creates a smart grid for enterprise data Pluggable End-Points Use existing change data capture logs with agents near the data Relational, Big Data, Cloud Services Pre-Built, SDK, message bus connectors Transaction Grid Resilient & secure scale-out architecture that guarantees transactional consistency Source DB is always source of truth with same commit timeline for all destinations 1:1, 1:N, N:1, and N:M topologies Policy Engine Declarative language to configure topology & over-the-wire services Selective data filters by row, column, schema Transform, mask/obfuscate, object mapping

8 Easy SaaS user experience

9 Multi-node grids with choice of topologies

10 How works: decoupled grid end points Pulls Changes Events From DB Logs with Minimal Overhead Each Consumer Pulls Data from Publisher Independently for Scale and HA Fetcher Plugin Relay Publisher Consumer Plugin Source Timeline Consistency & Neutral Format Consumer Plugin Destination Policy Policy Policy Policy Fetcher Policy (limit data read) Publisher Policy (limit data stored) Consumer Request Policy (limit data served) Consumer Policy (configure application)

11 Declarative policy language Replaces heavily customized database engineering scripts Powerful and expressive to include everything needed to configure the grid Optionally nested to enable the creation of hierarchical policies Dynamically updated without service interruption Define and tag groups of similar data, like personal data, and use tags in policy definitions Policy components Example

12 Using with Oracle GG installations On-Premise Public Cloud GoldenGate Extract GoldenGate Replicat Griddable Relay 12

13 Register now for the free beta! 13