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BEIJING, July 22, 2014--companies are looking for innovative ways to manage as many data and data sources as possible. While technologies such as Hadoop and NoSQL provide specific ways to deal with large data problems, these technologies may introduce islands of data that can complicate data access and data analysis needed to form critical insights. In order to maximize the value of information and better handle large data, organizations need to progressively change the data management architecture into large data management systems to seamlessly integrate various sources, all types of data, including Hadoop, relational databases, and NoSQL. While simplifying all data access, large data management systems should also help enterprises to leverage their existing skills, maintain enterprise-level data security and data governance capabilities, and protect sensitive information to meet regulatory requirements. to meet business needs and provide comprehensive data solutions, Oracle has launched Oracle Big Data sql. The product is an extremely important part of a large data management system. Oracle large data SQL has opened up islands of data and streamlined information access and discovery processes to help customers run the same SQL query across Hadoop, NoSQL, and Oracle databases to minimize data movement while improving performance and minimizing data island problems. Oracle large data SQL enables customers to discover depth information more easily and quickly, helping customers gain competitive advantage while protecting data security and complying with data governance policies. In addition, Oracle Large data SQL enables organizations to take full advantage of staff's existing SQL skills and existing investments in SQL applications. Oracle launches Oracle large data SQL. This sql-based software allows seamless integration of data across Hadoop, NoSQL, and Oracle databases. Oracle large data SQL runs on Oracle large data machines (Oracle Big Appliance) and can be used in conjunction with Oracle Exadata database cloud servers. By using industry-standard SQL connectivity-proven technologies to simplify information access, Oracle Large data SQL can help businesses view all enterprise data, discover deeper information more quickly, and further help businesses change their business. With its unique architecture and legacy intelligent scanning (smart Scan) technology from Oracle Exadata, Oracle Large Data SQL is able to query various forms of structured and unstructured data while minimizing data movement, significantly improving the distribution of Hadoop, NoSQL and the analysis speed of various data in Oracle database. Oracle large data SQL can also help enterprises take full advantage of the people's existing SQL skills, without paying a large fee to recruit new, maximize miningThe potential of existing technology investments. Oracle database security features, including the enterprise's existing security policy, have been extended to Hadoop and NoSQL data through Oracle Large data SQL. Oracle large data SQL is scheduled to be available in fall 2014. After increasing Oracle's large data SQL, Oracle large data solutions can help customers find useful information faster, make accurate predictions, simplify large data access, manage large data, and protect large data security. Quickly find valuable information and make accurate predictions because of the ability to use SQL to query and analyze data across the entire data management system, enterprises no longer need to: replicate and move data between platforms; Analyze data through MapReduce language Create a separate query for each platform, and then find the connection between the query structures. Pass on the intelligent scanning technology from Oracle Exadata to execute in a native way, intelligently discover the data needed for an established query to minimize data movement and improve performance. Oracle Large data SQL provides SQL based popular business intelligence tools and applications that make it easier to access Hadoop and nosql data sources outside of traditional data warehouses, so that valuable information and the operability of large data insights can be discovered faster without changing existing applications and tools. Simplifying large data access getting large data into your business requires the most new technologies, languages and skills. Oracle consolidates relational and non relational technologies into a single architecture and introduces industry-standard data Access language SQL, thus simplifying enterprise access to large data. By extending SQL to the entire data ecosystem of the enterprise, organizations can leverage the existing SQL skills of people to discover and analyze all data. Consolidate data management with Oracle Integrated systems, achieve rapid deployment and lower total cost of ownership of Hadoop, relational databases, and NoSQL data to help customers instantly enhance their data insights. Data governance and security Oracle Large data machines provide comprehensive data encryption capabilities to protect data privacy and meet regulatory requirements. With static data and network encryption, sensitive and regulated information stored on Oracle's large data machines is protected from theft or illegal access. Oracle Large data machines also provide enterprise-level authentication (Kerberos), Authorization (LDAP and Apache Sentry projects), and auditing (Oracle Audit Vault and Database firewall). These features can be set automatically at installation time, which greatly simplifies the Hadoop hardening process. To further ensure that enterprises give full play to large data advantages without impacting data governance, Oracle Large data machines extend Oracle database Advanced security capabilities to Hadoop and NOSQL data. With Oracle large data SQL, customers can leverage sophisticated Oracle database security solutions to achieve data deletion, privileged analysis, and powerful control over privileged user data access. With Oracle large data SQL, customers can now apply existing data security policies to data in Hadoop and NoSQL to strengthen enterprise governance and protect sensitive and regulated data. "Companies are increasingly using diverse data sources outside of relational databases, such as Hadoop and NoSQL," said Andrew Mendelsohn, executive vice president of Oracle and partner executives Oracle database technology products. As a result, the problem of islands of data is becoming more and more serious, which not only hinders data analysis and insight, but also leads to the inability of large data to exert real potential. Oracle large data SQL uses the popular and mature SQL query Language, eliminates the data island problem, and eventually pushes the big data into the enterprise mainstream application. Oracle continues to be a leader in database innovation, providing a simple but powerful way for businesses to access all data, leverage existing investment and personnel skills, and gain new value and insight into business change. "The Oracle Big Data machine is an ideal choice if customers want to adopt the Cloudera full set of Hadoop technologies," said Mike Olson, founder, chief strategist and chairman of Cloudera. Compared to DIY clusters, it is more cost-effective and faster to deploy. As for querying the data in Hadoop, we see that customers have a strong need for SQL. This is also the reason for Cloudera to develop Impala, Oracle has put Impala into Oracle Big Data machine. Impala enables customers to efficiently query the data in Hadoop in a native way with SQL. Customers can use Oracle Large data SQL that supports HDFS if they need to simultaneously query and analyze data residing in Hadoop and Oracle databases. Oracle Large data SQL also allows for continued use of existing SQL skills and security policies, and the integration of Hadoop with the existing Oracle infrastructure is easier. ”
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