Recent study NoSQL read some information

After completing one of the biggest projects of the year, the focus was on switching from PM roles to storage-related work, so it took some time outside of the work to focus on NoSQL related information (mainly from blog.nosqlfan.com)

NoSQL related

[Translate] NoSQL ecosystem

Http://blog.nosqlfan.com/html/2171.html

This is the best, most complete document I've seen NoSQL.

My understanding of NoSQL

http://www.dbthink.com/?p=687

Agree with the author's point of view, in the face of massive data, MySQL basically degenerate into a simple kv storage

NoSQL Product Classification Chart

Http://blog.nosqlfan.com/html/530.html

Auto-sharding doesn't quite understand.

SMAQ Architecture of mass data processing-storage, MapReduce and Query

Http://blog.nosqlfan.com/html/652.html

Isn't this the integration of storage retrieval we've been trying to implement?

BigTable models used in Cassandra and HBase

Http://blog.nosqlfan.com/html/704.html

Finally know what is column-oriented storage, and the knowledge of data consolidation

Unlike an ordinary RDBMS, a common RDBMS is usually row-type, with one row of data on a continuous disk space. Column storage is a sequential storage of each column. That's why it does not take up too much space to process null fields in fields. can also support flexible and loosely defined column definitions. That's what we usually call schema-less.

NoSQL theory-memory is the new hard drive, the hard disk is the new tape

Http://blog.nosqlfan.com/html/683.html

The cornerstone of NoSQL storage

About NoSQL-Why do we want to optimize the write performance of storage?

Http://blog.nosqlfan.com/html/737.html

Looking at the essence through the phenomenon, thinking about NoSQL is in place

In many of NoSQL's products, what we can see through benchmark is an extremely high write performance, with no significant gains in read performance or even a decline in the traditional RDBMS.

Database performance optimization based on SSD

Http://blog.nosqlfan.com/html/917.html

For a large number of randomly read key-value, the change of SSD can generally improve the TPS about 10 times times, the response time is basically reduced by 1/4

Learn about NoSQL's required readings

Http://hi.baidu.com/pkugsis/blog/item/99358dcb347bb5f153664fff.html

Are NoSQL's basic papers, and have time to read them carefully.

Redis related

Sharp Redis

Http://blog.nosqlfan.com/html/129.html

Getting started must look

Redis Concurrency Performance Test benchmark

Http://blog.nosqlfan.com/html/538.html

Maximum in 120,000, do not know whether it is a stand-alone, do not know is QPS or TPS, concurrent number after 4k began to decline, but slow down

Some misunderstandings in Redis

Http://blog.nosqlfan.com/html/868.html

AOF aims primarily at data reliability and high availability, there is another way to achieve the goal in Redis: Replication. Because of the high performance of Redis, there is no delay in replication. This achieves the prevention of a single point of failure and the implementation of high availability.

Mogodb related

Simple MongoDB

Http://blog.nosqlfan.com/html/219.html

PPT does well, it is worth learning ^_^

MongoDB MapReduce

Http://blog.nosqlfan.com/html/469.html

Map reduce Compare full reference

Vernacular MongoDB (i)

Http://www.ningoo.net/html/2011/mongodb_in_a_nutshell_1.html

It's pretty straightforward.

Performance test: MongoDB vs. sql Server

Http://blog.nosqlfan.com/html/484.html

The result is that MongoDB is about 10 times times faster than SQL Server, update is about 20 times times faster, and the select is about twice times faster.

Use of indexes in MongoDB

Http://blog.nosqlfan.com/html/271.html

MongoDB's index is very detailed, but MongoDB's index is very much like the RDBMS index, so it's easy to understand.

MongoDB Cluster

Http://blog.nosqlfan.com/html/544.html

Sharding, if the MongoDB query data is distributed across multiple nodes, where does the merge process work?

Foursquare up to 11 hours of downtime

Http://blog.nosqlfan.com/html/696.html

Cassandra myth shattered, MongoDB also have problems, NoSQL still have king? or no diamond.

HBase related

Getting Started with HBase

http://labs.chinamobile.com/mblog/4110_22332

It's really easy to read, mainly column, column faimly understanding

HBase Introduction

http://www.tbdata.org/archives/1509

Write well, read a lot of things, but still have a lot of questions

hbase-Introduction

Http://www.doc88.com/p-80782858011.html

The foreigner's HBase introduction, remembers one point: understands the column as the tag, but the value can be any length size

Summary of Oschina hbase data

Http://www.oschina.net/question/tag/hbase

HBase related content is also a lot, haven't seen

A PPT about HBase

Http://blog.nosqlfan.com/html/464.html

It's very detailed, probably the same as I understand.

HBase Level two index and join

Http://kenwublog.com/hbase-secondary-index-and-join

I don't know much, but I can see that HBase's support for level two indexing is very difficult.

Comparison of main design ideas of Cassandra and HBase

Http://kenwublog.com/cassandra-and-hbase-design-pattern-compar