Graph Database Query Language

As a software developer or DBA, one of the essential tasks is to deal with databases, such as MS SQL Server, MySQL, Oracle, PostgreSQL, MongoDB, and so on. As we all know, MySQL is currently the most widely used and the best free open source database, in addition, there are some you do not know or useless but excellent open source database, such as PostgreSQL, MongoDB, HBase, Cassandra, Couchba ...

It was easy to choose a database two or three years ago. Well-funded companies will choose Oracle databases, and companies that use Microsoft products are usually SQL Server, while budget-less companies will choose MySQL. Now, however, the situation is much different. In the last two or three years, many companies have launched their own Open-source projects to store information. In many cases, these projects discard traditional relational database guidelines. Many people refer to these items as NoSQL, the abbreviation for "not only SQL." Although some NoSQL number ...

In the current enterprise IT architecture, system administrators and DBAs will consider using the NoSQL database to solve problems that the RDBMS cannot solve, especially the internet industry. Traditional relational databases store data mainly as tables (table), and cannot meet the challenge of unstructured data. In the process of data standardization, the performance of relational database is encountering bottleneck. NoSQL, as its name suggests, is Not-only SQL, which can be a good complement to relational databases. In the report before the TechTarget database, ...

In the past few years, relational databases have been the only choice for data persistence, and data workers are considering only filtering in these traditional databases, such as SQL Server, Oracle, or MySQL. Even make some default choices, such as using. NET will typically choose SQL Server, and Java may be biased toward Oracle,ruby, Mysql,python is PostgreSQL or MySQL, and so on. The reason is simple: In the past a long time, the relational database is robust ...

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Hadoop is often identified as the only solution that can help you solve all problems. When people refer to "Big data" or "data analysis" and other related issues, they will hear an blurted answer: hadoop! Hadoop is actually designed and built to solve a range of specific problems. Hadoop is at best a bad choice for some problems. For other issues, choosing Hadoop could even be a mistake. For data conversion operations, or a broader sense of decimation-conversion-loading operations, E ...

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...

Large data areas of processing, my own contact time is not long, formal projects are still in development, by the large data processing attraction, so there is the idea of writing articles. Large data is presented in the form of database technologies such as Hadoop and "NO SQL", Mongo and Cassandra. Real-time analysis of data is now likely to be easier. Now the transformation of the cluster will be more and more reliable, can be completed within 20 minutes. Because we support it with a table? But these are just some of the newer, untapped advantages and ...

In the past few years, the innovative development of the open source world has elevated the productivity of Java™ developers to one level. Free tools, frameworks and solutions make up for once-scarce vacancies. The Apache CouchDB, which some people think is a WEB 2.0 database, is very promising. It's not difficult to master CouchDB, it's as simple as using a Web browser. This issue of Java open ...

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Doug cutting is based on Google's published academic paper. Users can easily develop and run applications that process massive amounts of data in Hadoop without knowing the underlying details of the distribution. The features of low cost, high reliability, high scalability, high efficiency and high fault tolerance make Hadoop the most popular large data analysis system, yet its HDFs and mapred ...