Cloud Computing Week Jevin Review (3.12-17)

Five major database models

Both relational and non relational databases are implementations of some kind of data model. This article will give you a brief introduction of 5 common data models, so that we can trace back to the mysterious world behind the current popular database solutions.

1. Relationship Model

The relational model uses records (composed of tuples) to store, records stored in tables, and tables are defined by the schema. Each column in the table has a name and a type, and all records in the table conform to the table definition. SQL is a specialized query language that provides the appropriate syntax for finding records that match criteria, such as table joins (join). Table joins can query records between multiple tables based on the relationships between tables.

2. Key value Storage

Key-value stores provide a way to access values based on key pairs.

Key-value pairs can be created or deleted, and the values associated with the keys can be updated.

Key-value stores generally do not provide transaction processing mechanisms.

3. Document Storage

Document storage supports access to structured data, unlike relational models, where there is no mandatory schema for document storage.

In fact, the document store is stored in the form of a packet key value pair. In this case, the application uses a few conventions for the packets to be retrieved, or the ability of the storage engine to divide the different documents into different collections to manage the data.

4. Column-Type storage

If you flip the data, the column store will be very similar to the relational store. Unlike a relational model store record, a column store stores all of the data in a column in a streaming fashion. For any record, the index can quickly get the data on the column.

5. Graphics Database

The graphics database stores vertex and edge information, and some supports adding annotations.

Five graphics databases to focus on

Graphic database is a kind of non relational database, it applies graph theory to store the relation information between entities. One of the most common examples is the relationship between people in social networks. Relational databases are not good for storing "relational" data, their queries are complex, slow, and beyond expectations, and the unique design of a graphics database compensates for this flaw.

Google's graphics computing system named Pregel, let's introduce you to a few popular graphics databases.

1. neo4j

Neo4j is a popular graphics database, it is open source.

2. Flockdb

FLOCKDB is built by Twitter for relational data analysis. FLOCKDB has so far not had a stable version, and it is debatable whether it is a real graphics database.

3. Allegrograph

Allegrograph is a graphics database built for the resource Description framework based on the standard of the consortium. It is designed to handle linked data and web semantics, and supports SPARQL, rdfs++, and Prolog.

4. Graphdb

Graphdb is a German sones company built on. Net. Graphdb hosted on Windows Azure platform.

5. Infinitegraph

Infinitegraph is based on the Java implementation, its goal is to build a "distributed graphics Database", has been used by the U.S. Department of Defense and the United States Central Intelligence Agency.

Next-generation Hadoop strategy-data platform

At last week's strata conference, participants revealed news about the next generation of Hadoop. This includes support for 6000 nodes, HDFs with high availability, and the characteristics of the next generation of MapReduce. And the bold idea of the future of Hadoop as an alternative to the operating system also fills us with endless reverie.

At the strata meeting, Hortonworks founder and VP of the Apache Hadoop project Arun Murthy revealed the features of the new version of Hadoop. The next generation of Hadoop will support 6000 nodes with a high-availability HDFs (Hadoop distributed File System).

The next-generation MapReduce framework is named yarn or MRv2 (MapReduce version 2). The new framework is no longer a traditional mapreduce framework, not even mapreduce, and yarn can be viewed as a generic runtime framework in which users can write their own computing frameworks to run in that run environment. The improved MapReduce will separate the management of blocks and namespaces in HDFs and improve the scalability of the data. Most importantly, the improved MapReduce will support mapreduce applications, which will enable more types of applications to be able to work in MapReduce.

Google algorithm uncovered: A search request for an average round-trip 2400 km

Google search Evolution

As the world's most widely used search engine, Google algorithm has been a layer of mystery. Recently, Google Engineering director Scott Hoffman to Tencent Technology to tell the story of Google algorithm behind the scenes, said more than 520 improvements in 2011 years, since 2003 to now, Google search has resolved 450 billion search requests.

Scott also revealed that a Google search request for an average round-trip distance between the computer and data center is 750 miles, which means that a search request average round-trip needs 1500 miles, about 2400 kilometers.

RavenDB: Based on windows/. NET Platform NoSQL database

As we all know, the NoSQL movement aims to be a substitute for the traditional relational database management system in the large data age. Ravendb is a good example of how Microsoft has changed its approach to open source today. The recognition of RAVENDB (NoSQL database) by Microsoft has surprised many people. Ravendb can easily replace the relational database management system and compatible with previous. NET Applications.

Ravendb is for windows/. NET platform. The presence of RAVENDB connects the. NET application with the non-relational database. Data is stored shcema-less and connected directly via HTTP, RESTful APIs, or more convenient. NET client APIs. NET Client API RAVENDB database document storage using LINQ operations.

Cloud computing: Who sits on Amazon's first and second place?

Amazon's Web service to users makes it the largest cloud service provider ever. Like most large cloud providers, Amazon does not disclose too much about current or planned data centers.

The latest study by Accenture analyst Huan Liu shows that Amazon's elastic Compute Cloud (EC2) runs on up to 450,000 servers. Amazon has not released AWS revenue, but some say it may already be a 1 billion-dollar business.

This article is expected to Rackspace, Google, Microsoft, IBM, HP, VMware, Facebook seven companies will become Amazon's cloud rivals.

Xinmi Key technology simplifies cloud data encryption

Because the IT team lacks direct control of data security in a cloud environment, data migration to the cloud will bring new and complex security issues to the IT team. In addition, cloud providers consider data security to be a shared responsibility, that is, that the service provider guarantees physical security and that users must secure their servers and data. This will require new encryption policies and key management policies that store the keys outside the cloud environment, not the cloud environment.

Porticor, a start-up security company, has just unveiled a solution that addresses static data security issues in the cloud environment. Porticor offers a separate key encryption solution, and cloud clients are the only ones who know the master key. In addition, the Porticor company solves all the complex problems associated with encrypting data, and the customer hardly thinks about these issues. This unique Key management solution provides both security and convenience.

Microsoft Cuts Azure cloud service price to rival Amazon

Microsoft slashed its Azure cloud storage service and the price of Windows Azure Extra Sgt Computing Services last week. The move follows a few days after Amazon downgraded its Web services price.

What does all this mean? For it buyers, cloud computing prices are falling rapidly and are already at the same level as electricity tariffs. The price of cloud computing may be cheaper, given that electricity is affected by natural gas prices, seasons and other variables.