Traditionally, the term "database" as used by technical professionals implied "relational, row-based, transactional." These implied extra characteristics do us a disservice when speaking of databases in a high-volume environment where there must be several types of databases deployed, some of which aren't relational, some of which aren't row-based, and most of which aren't transactional.
When we initially started our 更多相关的内容 »
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There's been a lot of new articles about Cassandra deployments in the past month, enough that I thought it would be useful to summarize in a post.
Ryan King explained in an interview with Alex Popescu why Twitter is moving to Cassandra for tweet storage, and why they selected Cassandra over the alternatives. My experience is that th
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Cassandra is a hybrid non-relational database in the same class as Google's BigTable. It is more featureful than a key/value store like Dynomite, but supports fewer query types than a document store like MongoDB.
Cassandra was started by Facebook and later transferred to the open-source community. It is an ideal runtime database for web-sca
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Perhaps you’re considering using a dedicated key-value or document store instead of a traditional relational database. Reasons for this might include:
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I’m doing word and bigram counts on a corpus of tweets. I want to store and rapidly retrieve them later for language model purposes. So there’s a big table of counts that get incremented many times. The easiest way to get something running is to use an open-source key/value store; but which? There’s recently been some development in this area so I thought it would be
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在本文中的HBase术语:
基于列:column-oriented
行:row
列组:column families
列:column
单元:cell
理解HBase(一个开源的Google的BigTable实际应用)最大的困难是HBase的数据结构概念究竟是什么?首先HBase不同于一般的关系数据库,它是一个适合于非结构化数据存储的数据库.另一个不同的是HBase基于列的而不是基于行的模式.
Google's BigTable论文清楚地解释了什么是BigTable:
Bigtable是一个疏松的分布式的持久的多维排序的map,这个map被行键,列键,和时间戳索引.每一个值都是连续的byte数组.(A Bigtable is a sparse, distributed, persistent multidimensional sorted map. The map
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A few weeks ago, I wrote a post describing the drive behind the demand for a new form of database alternatives, often referred to as NOSQL. A few weeks ago during my Qcon presentation, I went through the patterns of building a scalable twitter application, and obviously one of the interesting challenges that we discussed is the database scalabili
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最近关注Hadoop,因此也顺便关注了一下Hadoop相关的项目。HBASE就是基于Hadoop的一个开源项目,也是对Google的BigTable 更多相关的内容 »
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This is the story of how I learned to say ‘No’ to SQL and to cope with my wife’s addiction to Coach bags.
The answer is support groups. I kid. No, I don’t.
There are a number of alternatives to relational databases. However, for the purposes of this post, I am focusing on persistent, distributed key/value stores.
It all seems to have started with Amazon’s 更多相关的内容 »
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The days of the relational database being a one-stop-shop for all of your persistence needs are over. A new class of application is beginning to emerge with requirements that exceed the capabilities of the relational database. Some of these applications need unlimited scalability or bullet proof fault tolerance, while others may require blazing fast access or flexible data storage. The relational database was simply not designed to meet the needs of this small but growing class. Instead, a n
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There have been confirmed rumors[1] about Twitter planning to use Cassandra for a long time. But except the mentioned post, I couldn’t find any other references.
Twitter is fun by itself and we all know that NoSQL projects love Twitter. So, imagine how excited I was when after posting
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There is a dark side to most of the current NoSQL databases. People rarely talk about it. They talk about performance, about how easy schemaless databases are to use. About nice APIs. They are mostly developers and not operation and system administrators. No-one asks those. But it’s there where rubber hits the road.
The three problems no-one talks about – almost noone, I had a good talk with the Infinispan lead [1] – are:
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A lot of the problems we had to tackle in the last months were directly related to the data stores we used, as well as the schema of the objects we stored.
We’ve been using MySQL and Memcached from day one, because it’s always good when you have 50 different problems to tackle to use tools that you know (read
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There are many current and emerging products that can be considered as suitable for storing and managing data. This list is an attempt to identify popular products that existing organizations that use MySQL may consider as alternative
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I've been playing recently with several distributed databases with the aim of choosing the best solution for my needs. Since there isn't much documentation on the web with a general overview on the subject, I write here some comments, thoughts and my humble experience. Hope it's usefull for you, this document is not a comparison of performance, or a "mine is bigger than yours", just some ideas ;)
My background
Being my experience based on relatio
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Last week I ended up building a distributed keystore for a client. That wasn’t my original intention, but after doing testing on just about every project out there, it turned out to be the best (only?) solution for our needs.
Specifically, a production environment handling at least 100M items with an accelerating growth curve, very low latency retrievals, and the ability to handle 100s of inserts/s w/ variable-sized data (avg 1K, but up in many cases well beyond) … on EC2
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Revolutionary open-source distributed DBMS eliminates price/performance and scalability barriers, keeps SQL and ACID
Billerica, Mass., May 25, 2010 – VoltDB, LLC, announced today the general availability of the VoltDB OLTP database management system (DBMS). Under the leadership of Postgres and Ingres co-founder, Mike St
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Designing responsive web interfaces for analyzing short read data requires techniques to rapidly retrieve and display all details associated with a read. My own work on this has been relying heavily on Berkeley DB key/value databases. For example, an analysis will have key/value stores relating the read to aligned positions in the genome, counts of reads found in a sequencing run, and other associated metadata. <
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