Oracle Large Data machine using Oracle Audit Vault and Database firewall

Source: Internet
Author: User
Keywords Large data machine Audit database firewall

Oracle Global Congress, September 24, 2013-Bringing large data into the business can create opportunities for business change, but the growing number and complexity of large data can also pose challenges. With Oracle Unified information architecture, customers can easily and economically integrate Hadoop and NoSQL platforms with data warehousing and business Analytics solutions to maximize the value of large data. Although Hadoop provides an extensible foundation for large data projects, the lack of intrinsic security has been an obstacle to many enterprises adopting Hadoop. To address this problem, Oracle has enhanced the capabilities of Oracle's large data machines, incorporating enterprise-class security features for Hadoop. Oracle will also launch a new Oracle large Data connector and Oracle NoSQL database, which will enhance the functionality, performance, and scalability of these new products.

Oracle Large data machines now employ Oracle Audit Vault and data firewalls, enabling pre-configured Kerberos authentication, LDAP based authorization, and reliable centralized auditing to provide integrated enterprise security.

By consolidating and analyzing the Hadoop audit trail, Oracle Audit Vault and database firewalls can alert you to suspicious or unauthorized activity in accordance with predetermined policies. In addition, consolidated audit data can help companies display control initiatives, resulting in compliance and reporting requirements for audits.

Oracle Large data machines now include feature updates for Hadoop, upgraded Oracle large data connectors, and Oracle NoSQL databases that improve performance and scalability, and simplify management to help users quickly manage and analyze large data without any difficulty, At the same time minimizing risk. The update features include:

Working with XQuery in Hadoop: Oracle XQuery for Hadoop is new to Oracle's large data connectors, implementing standard XQuery operations to process and transform XML files, which can be executed in parallel across the Hadoop cluster.
Enhanced Predictive Modeling: The Oracle R Connector for Hadoop adds a generalized linear model and a factor analysis algorithm that improves performance by 5 times times the customized R-MapReduce, enabling businesses to quickly build complex predictive models with large data.
Faster Hadoop processing: the perfect balance (Perfect Balance) is a new high-performance component of the Oracle large data machine, which intelligently detects data distortions, balances the reducer load, and enables MapReduce operations to execute faster.
Higher NoSQL performance and scalability: The latest version of the Oracle NoSQL database is available, which allows for parallel data scans, significantly reducing the time required for database scans. Oracle NoSQL databases now support features that customers need, such as supporting multiple data centers to simplify and automate data allocation.

Oracle Executive Introduction

"For big Data management, Hadoop and NoSQL databases have proven to be groundbreaking technologies," said Çetinözbütün, senior vice president of Oracle's Data Warehouse and big data technology. However, most of the solutions on the market do not meet the requirements of the enterprise, because security in the enterprise is absolutely necessary, and security can not be compromised. With the latest enhancements to Oracle's large data machines, Oracle delivers the enterprise-class security and performance that customers require for large data solutions. ”

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