New technologies bridge the gap between Oracle, Hadoop, and NoSQL data stores

All along, the use of big data is far less than the big data collection ability, the main reason is that the current enterprise data is mainly scattered in different systems or organizations, big Data strategy is to be able to more depth, more abundant mining all data system valuable information, so as to more accurately predict customer behavior, find business value, However, it is difficult to move this data to a separateData storage, security and regulatory issues are not guaranteed, and Oracle Big data SQL launches address the challenges that are now facing.

The following are the translations:
Discovering the needs of a business or organization for a data management architecture, Oracle launches Big Data SQL software to consolidate a wide variety of data sources, including Hadoop, NoSQL, and Oracle databases.
A complete solution is to combine Oracle's big Data device and big SQL, Cloudera's Hadoop distributed and Oracle's own NoSQL database. Initially Oracle Big Data SQL supports only Apache hive and the Hadoop File System, and other vendors need to migrate the SQL relational database to run on Hadoop.

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Oracle offers a complete suite of solutions for big data devices and large database SQL

Oracle Big Data SQL products mean that administrators are not required to learn other query languages when dealing with information in a non-relational database or Hadoop, says Neil Mendelson, Oracle's head of analytics.

We can use the Oracle SQL language we're accustomed to--the full SQL language, and we can now directly access any of these three data sources or any combination of them, he explains.
Similar tools are available in the open source community such as Stinger, which allows you to query data in Hadoop using SQL commands, or use the CQL language (Cassandra Query language) designed to implement SQL commands on NoSQL systems.

The goal of creating this big data management system is to want SQL queries to run on different data sources and enable enterprises or organizations to leverage existing technologies to maintain enterprise-classdata security, and managing sensitive information. Oracle says the technology's unique architecture and smart scan inherit from Oracle Exadata, while allowing Oracle BIG data SQL to query all forms of structured and unstructured data and minimize data movement.

This also facilitates the security capabilities of Oracle databases, including the organization of existing security policies to extend to Hadoop and NoSQL data.

Oracle's Dan McClary says the product has been in development for some time, and it goes beyond the existing technology. He also indicated that big Data SQL was able to co-resident with HDFs datanodes and yarn nodemanagers, and that queries from new external tables were sent to these services to ensure direct path reading and data localization.

"The software set that runs Cloudera on Oracle's Big data devices is more cost-effective and faster than a DIY cluster deployment," said Mike Olson, founder, chairman and chief strategy officer of Cloudera. In Hadoop querying data, we have seen a strong customer demand for SQL. "

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New technologies bridge the gap between Oracle, Hadoop, and NoSQL data stores