Sql Querying Skills

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Oracle to launch Oracle Big Data sql

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, enterprises need to gradually change the data management architecture into a large data management system to seamlessly integrate various sources, all types of data, including Hadoop, relational databases, and nos ...

Introducing IBM's SQL technology for Hadoop to relational DBMS users

This article will introduce big SQL, which answers many common questions about this IBM technology that users of relational DBMS have. Large data: It is useful for IT professionals who analyze and manage information. But it's hard for some professionals to understand how to use large data, because Apache Hadoop, one of the most popular big data platforms, has brought a lot of new technology, including the newer query and scripting languages. Big SQL is IBM's Hadoop based platform Infosphere Biginsight ...

MapR trying to push sql-on-hadoop to new levels

MAPR today updated its Hadoop release, adding Apache Drill 0.5 to reduce the heavy data engineering effort. Drill is an open source distributed ANSI query engine, used primarily for self-service data analysis. This is the open source version of Google's Dremel system, which is used primarily for interactive querying of large datasets-which support its bigquery servers. The objective of the Apache Drill project is to enable it to scale to 10,000 servers or more servers, while processing in a few seconds ...

Microsoft Azure Hadoop features Overview

As we all know, the big data wave is gradually sweeping all corners of the globe. And Hadoop is the source of the Storm's power. There's been a lot of talk about Hadoop, and the interest in using Hadoop to handle large datasets seems to be growing. Today, Microsoft has put Hadoop at the heart of its big data strategy. The reason for Microsoft's move is to fancy the potential of Hadoop, which has become the standard for distributed data processing in large data areas. By integrating Hadoop technology, Microso ...

Optimized Hadoop distributions make hybrid architectures the past

Data is the most important asset of an enterprise. The mining of data value has always been the source of innovation of enterprise application, technology, architecture and service. After ten years of technical development, the core data processing of the enterprise is divided into two modules: the relational database (RDBMS), mainly used to solve the transaction transaction problem; Based on analytical Data Warehouse, mainly solves the problem of data integration analysis, and when it is necessary to analyze several TB or more than 10 TB data, Most enterprises use MPP database architecture. This is appropriate in the traditional field of application. But in recent years, with ...

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One to two years ahead of MongoDB. Build Enterprise-Class NoSQL database

Over the past few years, NoSQL database with its easy to expand, high-performance, high availability, data model flexibility and other features attracted a large number of emerging internet companies, including the domestic Taobao, Sina, Jingdong Mall, 360, Sogou, etc. have been in the local attempt to NoSQL solutions. Guangzhou giant FIR Database is a focus on the new NoSQL distributed database research and development of the start-up company, has now won the first round of angel investment, the core product is sequoiadb. The founding team members of the giant FIR database are from IBM North America Laboratories, and have long been engaged in the relational database D ...

Optimized Hadoop distributions make hybrid architectures the past

Data is the most important asset of an enterprise. The mining of data value has always been the source of innovation of enterprise application, technology, architecture and service. After ten years of technical development, the core data processing of the enterprise is divided into two modules: the relational database (RDBMS), mainly used to solve the transaction transaction problem; Based on analytical Data Warehouse, mainly solves the problem of data integration analysis, and when it is necessary to analyze several TB or more than 10 TB data, Most enterprises use MPP database architecture. This is appropriate in the traditional field of application. But in recent years, with the internet ...

Must read! Big Data: Hadoop, Business Analytics and more (2)

There are many methods for processing and analyzing large data in the new methods of data processing and analysis, but most of them have some common characteristics.   That is, they use the advantages of hardware, using extended, parallel processing technology, the use of non-relational data storage to deal with unstructured and semi-structured data, and the use of advanced analysis and data visualization technology for large data to convey insights to end users.   Wikibon has identified three large data methods that will change the business analysis and data management markets. Hadoop Hadoop is a massive distribution of processing, storing, and analyzing ...

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