high_scalability high_scalability-2009 high_scalability-2009-607 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Database Optimize patterns Most of websites and enterprise application rely on the database backing them to store the application and customer data. So at some point the database could be the main performance and scalability bottleneck for your system performance, so I ‘m here today to cure this! key points: Database supporters and resisters: Database supporters: MySQL, SQL Server, and PostgreSQL Database resisters: HBase, MongoDB, Redis, and others Database Optimizing pattern: What to store into the Database? Field data types The primary key and the indexes Data retrieve, SP’s, and Ad-hoc queries Caching
sentIndex sentText sentNum sentScore
1 Database Optimize patterns Most of websites and enterprise application rely on the database backing them to store the application and customer data. [sent-1, score-1.068]
2 So at some point the database could be the main performance and scalability bottleneck for your system performance, so I ‘m here today to cure this! [sent-2, score-0.971]
3 key points: Database supporters and resisters: Database supporters: MySQL, SQL Server, and PostgreSQL Database resisters: HBase, MongoDB, Redis, and others Database Optimizing pattern: What to store into the Database? [sent-3, score-0.776]
wordName wordTfidf (topN-words)
[('resisters', 0.561), ('supporters', 0.527), ('cure', 0.228), ('database', 0.206), ('backing', 0.172), ('retrieve', 0.17), ('store', 0.134), ('optimizing', 0.133), ('rely', 0.133), ('field', 0.131), ('hbase', 0.131), ('bottleneck', 0.122), ('pattern', 0.121), ('key', 0.115), ('redis', 0.109), ('optimize', 0.106), ('mongodb', 0.106), ('primary', 0.105), ('points', 0.095), ('main', 0.095), ('customer', 0.094), ('websites', 0.088), ('enterprise', 0.087), ('today', 0.081), ('sql', 0.08), ('application', 0.077), ('performance', 0.064), ('mysql', 0.061), ('point', 0.057), ('could', 0.045), ('scalability', 0.044), ('server', 0.037), ('system', 0.029), ('data', 0.021)]
simIndex simValue blogId blogTitle
same-blog 1 1.0 607 high scalability-2009-05-26-Database Optimize patterns
Introduction: Database Optimize patterns Most of websites and enterprise application rely on the database backing them to store the application and customer data. So at some point the database could be the main performance and scalability bottleneck for your system performance, so I ‘m here today to cure this! key points: Database supporters and resisters: Database supporters: MySQL, SQL Server, and PostgreSQL Database resisters: HBase, MongoDB, Redis, and others Database Optimizing pattern: What to store into the Database? Field data types The primary key and the indexes Data retrieve, SP’s, and Ad-hoc queries Caching
2 0.11443169 658 high scalability-2009-07-17-Against all the odds
Introduction: This article not about Mariah Carey, or its song. It's about Storing System, Database. First let's describe what means by odds: In my social network, I found 93% of the mainstream developers sanctify the database, or at least consider it in any data persistence challenge as the ultimate, superhero, and undefeatable solution. I think this problem come from the education, personally, and some companies also I think it's involved in this. To start to fix this bad thinking, we all should agree in the following points: Every challenge have its own solutions, so whatever you want to save/persistent, there are always many solutions. For example the Web search engines, such as: Google, Kngine, Yahoo, Bing don't use database at all instead we use Indexes (Index file) for better performance. The Database in general whatever the vendor it's slow compared with other solutions such as: Key-Value storing system, Index file, DHT. The Database currently employ Relation Data model
3 0.10731214 1303 high scalability-2012-08-13-Ask HighScalability: Facing scaling issues with news feeds on Redis. Any advice?
Introduction: We just released a social section to our iOS app several days ago and we are already facing scaling issues with the users' news feeds. We're basically using a Fan-out-on-write (push) model for the users' news feeds (posts of people and topics they follow) and we're using Redis for this (backend is Rails on Heroku). However, our current 60,000 news feeds is ballooning our Redis store to almost 1GB in a just a few days (it's growing way too fast for our budget). Currently we're storing the entire news feed for the user (post id, post text, author, icon url, etc) and we cap the entries to 300 per feed. I'm wondering if we need to just store the post IDs of each user feed in Redis and then store the rest of the post information somewhere else? Would love some feedback here. In this case, our iOS app would make an api call to our Rails app to retrieve a user's news feed. Rails app would retrieve news feed list (just post IDs) from Redis, and then Rails app would need to query to g
Introduction: You may have read somewhere that Facebook has introduced a new Social Inbox integrating email, IM, SMS, text messages, on-site Facebook messages. All-in-all they need to store over 135 billion messages a month. Where do they store all that stuff? Facebook's Kannan Muthukkaruppan gives the surprise answer in The Underlying Technology of Messages : HBase . HBase beat out MySQL, Cassandra, and a few others. Why a surprise? Facebook created Cassandra and it was purpose built for an inbox type application, but they found Cassandra's eventual consistency model wasn't a good match for their new real-time Messages product. Facebook also has an extensive MySQL infrastructure , but they found performance suffered as data set and indexes grew larger. And they could have built their own, but they chose HBase. HBase is a scaleout table store supporting very high rates of row-level updates over massive amounts of data . Exactly what is needed for a Messaging system. HBase is also a colu
5 0.10144125 410 high scalability-2008-10-13-SQL Server 2008 Database Performance and Scalability
Introduction: Microsoft SQL Server 2008 incorporates the tools and technologies that are necessary to implement relational databases, reporting systems, and data warehouses of enterprise scale, and provides optimal performance and responsiveness. With SQL Server 2008, you can take advantage of the latest hardware technologies while scaling up your servers to support server consolidation. SQL Server 2008 also enables you to scale out your largest data solutions. This white paper describes the performance and scalability capabilities of Microsoft速 SQL Server速 2008 and explains how you can use these capabilities to: * Optimize performance for any size of database with the tools and features that are available for the database engine, analysis services, reporting services, and integration services. * Scale up your servers to take full advantage of new hardware capabilities. * Scale out your database environment to optimize responsiveness and to move your data
6 0.090629235 1337 high scalability-2012-10-10-Antirez: You Need to Think in Terms of Organizing Your Data for Fetching
7 0.08621382 582 high scalability-2009-04-26-Poem: Partly Cloudy
8 0.080505282 292 high scalability-2008-03-30-Scaling Out MySQL
9 0.07984475 795 high scalability-2010-03-16-1 Billion Reasons Why Adobe Chose HBase
10 0.077754393 151 high scalability-2007-11-12-a8cjdbc - Database Clustering via JDBC
11 0.077279873 1606 high scalability-2014-03-05-10 Things You Should Know About Running MongoDB at Scale
12 0.076894358 1189 high scalability-2012-02-07-Hypertable Routs HBase in Performance Test -- HBase Overwhelmed by Garbage Collection
13 0.074717298 1514 high scalability-2013-09-09-Need Help with Database Scalability? Understand I-O
15 0.072562419 736 high scalability-2009-11-04-Damn, Which Database do I Use Now?
16 0.072180152 1064 high scalability-2011-06-20-35+ Use Cases for Choosing Your Next NoSQL Database
17 0.071276672 1646 high scalability-2014-05-12-4 Architecture Issues When Scaling Web Applications: Bottlenecks, Database, CPU, IO
18 0.070214979 1008 high scalability-2011-03-22-Facebook's New Realtime Analytics System: HBase to Process 20 Billion Events Per Day
19 0.069433972 1276 high scalability-2012-07-04-Top Features of a Scalable Database
topicId topicWeight
[(0, 0.096), (1, 0.026), (2, -0.035), (3, -0.025), (4, 0.047), (5, 0.109), (6, -0.008), (7, -0.081), (8, 0.039), (9, -0.002), (10, -0.018), (11, 0.011), (12, -0.01), (13, 0.052), (14, -0.033), (15, 0.008), (16, 0.005), (17, -0.033), (18, -0.024), (19, -0.044), (20, -0.016), (21, -0.019), (22, -0.023), (23, -0.022), (24, 0.064), (25, 0.007), (26, -0.021), (27, -0.012), (28, 0.038), (29, 0.028), (30, -0.004), (31, 0.015), (32, 0.054), (33, -0.005), (34, 0.021), (35, 0.022), (36, 0.016), (37, -0.0), (38, 0.019), (39, 0.006), (40, 0.02), (41, -0.07), (42, 0.008), (43, 0.055), (44, 0.039), (45, 0.025), (46, -0.006), (47, -0.016), (48, -0.017), (49, 0.057)]
simIndex simValue blogId blogTitle
same-blog 1 0.93761021 607 high scalability-2009-05-26-Database Optimize patterns
Introduction: Database Optimize patterns Most of websites and enterprise application rely on the database backing them to store the application and customer data. So at some point the database could be the main performance and scalability bottleneck for your system performance, so I ‘m here today to cure this! key points: Database supporters and resisters: Database supporters: MySQL, SQL Server, and PostgreSQL Database resisters: HBase, MongoDB, Redis, and others Database Optimizing pattern: What to store into the Database? Field data types The primary key and the indexes Data retrieve, SP’s, and Ad-hoc queries Caching
2 0.76190758 1054 high scalability-2011-06-06-NoSQL Pain? Learn How to Read-write Scale Without a Complete Re-write
Introduction: Lately I've been reading more cases were different people have started to realize the limitations of the NoSQL promise to database scalability. Note the references below: Why does Quora use MySQL as the data store instead of NoSQLs such as Cassandra, MongoDB, CouchDB etc? Why did Diaspora abandon MongoDB for MySQL? How scalable is CouchDB in practice, not just in theory? Take MongoDB for example. It's damn fast, but it doesn't really know how to save data reliably to disk. I've had it set up in a replica pair to mitigate that risk. Guess what - both servers in the pair failed and corrupted their data files at the same day. It appears that for many, the switch to NoSQL can be rather painful. IMO that doesn't necessarily mean that NoSQL is wrong in general, but it's a combination of 1) lack of maturity 2) not the right tool for the job. That brings the question of what's the alternative solution? In the following post I tried to summarize the lessons from
3 0.70633966 1025 high scalability-2011-04-16-The NewSQL Market Breakdown
Introduction: Matt Aslett from the 451 group created a term called “NewSQL ”. On the definition of NewSQL, Aslett writes: “NewSQL” is our shorthand for the various new scalable/high performance SQL database vendors. We have previously referred to these products as ‘ScalableSQL’ to differentiate them from the incumbent relational database products. Since this implies horizontal scalability, which is not necessarily a feature of all the products, we adopted the term ‘NewSQL’ in the new report. And to clarify, like NoSQL, NewSQL is not to be taken too literally: the new thing about the NewSQL vendors is the vendor, not the SQL. As with NoSQL, under the NewSQL umbrella you can see various providers, with various solutions. I think these can be divided into several sub-types: New MySQL storage engines . These give MySQL users the same programming interface, but scale very well. You can Xeround or Akiban in this field. The good part is that you still use MySQL, but on the downside it’s n
4 0.65254366 961 high scalability-2010-12-21-SQL + NoSQL = Yes !
Introduction: This is a guest post by Frédéric Faure (architect at Ysance ), you can follow him on twitter . Data storage has always been one of the most difficult problems to address, especially as the quantity of stored data is constantly increasing. This is not simply due to the growing numbers of people regularly using the Internet, particularly with all the social networks, games and gizmos now available. Companies are also amassing more and more meticulous information relevant to their business, in order to optimize productivity and ROI (Return On Investment). I find the positioning of SQL and NoSQL (Not Only SQL) as opposites rather a shame: it’s true that the marketing wave of NoSQL has enabled the renewed promotion of a system that’s been around for quite a while, but which was only rarely considered in most cases, as after all, everything could be fitted into the « good old SQL model ». The reverse trend of wanting to make everything fit the NoSQL model is not very p
5 0.64925581 782 high scalability-2010-02-23-When to migrate your database?
Introduction: Why migrate your database? Efficiency and availability problems are harming your business – reports are out of date, your batch processing window is nearing its limits, outages (unplanned/planned) frequently halt work. Database consolidation – remove the costs that result from a heterogeneous database environment (DBAs time, database vendor pricing, database versions, hardware, OSs, patches, upgrades etc.). OK, so the driving forces for migration are clear, what now? Read more on BigDataMatters.com
6 0.63567603 137 high scalability-2007-10-30-Database parallelism choices greatly impact scalability
7 0.63501513 151 high scalability-2007-11-12-a8cjdbc - Database Clustering via JDBC
8 0.63307726 736 high scalability-2009-11-04-Damn, Which Database do I Use Now?
9 0.63239324 455 high scalability-2008-12-01-MySQL Database Scale-out and Replication for High Growth Businesses
10 0.62524641 537 high scalability-2009-03-12-QCon London 2009: Database projects to watch closely
11 0.62309927 867 high scalability-2010-07-27-YeSQL: An Overview of the Various Query Semantics in the Post Only-SQL World
12 0.62273806 670 high scalability-2009-08-05-Anti-RDBMS: A list of distributed key-value stores
13 0.62214899 698 high scalability-2009-09-10-Building Scalable Databases: Denormalization, the NoSQL Movement and Digg
14 0.61884433 935 high scalability-2010-11-05-Hot Scalability Links For November 5th, 2010
15 0.61805451 655 high scalability-2009-07-12-SPHiveDB: A mixture of the Key-Value Store and the Relational Database.
16 0.61205101 784 high scalability-2010-02-25-Paper: High Performance Scalable Data Stores
17 0.61016899 799 high scalability-2010-03-23-Digg: 4000% Performance Increase by Sorting in PHP Rather than MySQL
18 0.60124099 1064 high scalability-2011-06-20-35+ Use Cases for Choosing Your Next NoSQL Database
19 0.59845179 1337 high scalability-2012-10-10-Antirez: You Need to Think in Terms of Organizing Your Data for Fetching
20 0.59518057 65 high scalability-2007-08-16-Scaling Secret #2: Denormalizing Your Way to Speed and Profit
topicId topicWeight
[(1, 0.236), (2, 0.09), (8, 0.278), (30, 0.089), (61, 0.13)]
simIndex simValue blogId blogTitle
1 0.89277792 354 high scalability-2008-07-20-The clouds are coming
Introduction: A report from the CloudCamp conference on cloud computing, held in London in July 2008.
2 0.88818532 272 high scalability-2008-03-08-Product: FAI - Fully Automatic Installation
Introduction: From their website: FAI is an automated installation tool to install or deploy Debian GNU/Linux and other distributions on a bunch of different hosts or a Cluster. It's more flexible than other tools like kickstart for Red Hat, autoyast and alice for SuSE or Jumpstart for SUN Solaris. FAI can also be used for configuration management of a running system. You can take one or more virgin PCs, turn on the power and after a few minutes Linux is installed, configured and running on all your machines, without any interaction necessary. FAI it's a scalable method for installing and updating all your computers unattended with little effort involved. It's a centralized management system for your Linux deployment. FAI's target group are system administrators who have to install Linux onto one or even hundreds of computers. It's not only a tool for doing a Cluster installation but a general purpose installation tool. It can be used for installing a Beowulf cluster, a rendering farm,
same-blog 3 0.84455007 607 high scalability-2009-05-26-Database Optimize patterns
Introduction: Database Optimize patterns Most of websites and enterprise application rely on the database backing them to store the application and customer data. So at some point the database could be the main performance and scalability bottleneck for your system performance, so I ‘m here today to cure this! key points: Database supporters and resisters: Database supporters: MySQL, SQL Server, and PostgreSQL Database resisters: HBase, MongoDB, Redis, and others Database Optimizing pattern: What to store into the Database? Field data types The primary key and the indexes Data retrieve, SP’s, and Ad-hoc queries Caching
4 0.84408164 858 high scalability-2010-07-13-Sponsored Post: VoltDB and Digg are Hiring
Introduction: Who's Hiring? VoltDB is Hiring Get Your High Scalability Fix at Digg VoltDB Field/Community Engineer VoltDB is attracting more and more users every day. If you have a strong technical background in SQL and Linux, are experienced with production database deployments, and have a passion for customers and community, you could be just the person we are looking for. Are you excited about the prospect of working with users to develop and deploy VoltDB applications, and about helping users participate in the thriving VoltDB community? If so, read on at their job page . Get Your High Scalability Fix at Digg Interested in working on cutting-edge high-scale infrastructure at Digg? We're making a big investment in scaling and have committed to the NoSQL (Not only SQL) path with Cassandra . We're using other open-source infrastructure to help us scale including Hadoop, RabbitMQ, Zookeeper, Thrift, HDFS and Lucene. We're rewriting Digg from the ground up and we need
5 0.77631193 833 high scalability-2010-06-01-Sponsored Post: Get Your High Scalability Fix at Digg
Introduction: Get Your High Scalability Fix at Digg Interested in working on cutting-edge high-scale infrastructure at Digg? We're making a big investment in scaling and have committed to the NoSQL (Not o nly SQL) path with Cassandra . We're using other open-source infrastructure to help us scale including Hadoop, RabbitMQ, Zookeeper, Thrift, HDFS and Lucene. We're rewriting Digg from the ground up and we need amazing developers to join our world-class team. If you think you are up for the challenge, or you know someone who might be, take a look at our jobs page for more information.
6 0.74551487 913 high scalability-2010-10-01-Hot Scalability Links For Oct 1, 2010
7 0.72218049 1108 high scalability-2011-08-31-Pud is the Anti-Stack - Windows, CFML, Dropbox, Xeround, JungleDisk, ELB
8 0.71918797 1243 high scalability-2012-05-10-Paper: Paxos Made Moderately Complex
9 0.70670319 1434 high scalability-2013-04-03-5 Steps to Benchmarking Managed NoSQL - DynamoDB vs Cassandra
10 0.69126683 90 high scalability-2007-09-12-Technology behind mediatemple grid service
11 0.68807626 186 high scalability-2007-12-13-un-article: the setup behind microsoft.com
12 0.68753099 377 high scalability-2008-09-03-SMACKDOWN :: Who are the Open Source Content Management System (CMS) market leaders in 2008?
15 0.68318963 570 high scalability-2009-04-15-Implementing large scale web analytics
17 0.67798197 395 high scalability-2008-09-25-Is your cloud as scalable as you think it is?
18 0.67679942 641 high scalability-2009-06-29-Google App Engine plus Amazon AWS: Best of both worlds
19 0.66997349 386 high scalability-2008-09-22-Cloud computing, grid computing, utility computing - list of top providers
20 0.66962612 629 high scalability-2009-06-14-CLOUD & GRID EVENT BY THE ONLINE GAMING HIGH SCALABILITY SIG