high_scalability high_scalability-2012 high_scalability-2012-1186 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: “ Data is everywhere, never be at a single location. Not scalable, not maintainable. ” –Alex Szalay While Galileo played life and death doctrinal games over the mysteries revealed by the telescope, another revolution went unnoticed, the microscope gave up mystery after mystery and nobody yet understood how subversive would be what it revealed. For the first time these new tools of perceptual augmentation allowed humans to peek behind the veil of appearance. A new new eye driving human invention and discovery for hundreds of years. Data is another material that hides, revealing itself only when we look at different scales and investigate its underlying patterns. If the universe is truly made of information , then we are looking into truly primal stuff. A new eye is needed for Data and an ambitious project called Data-scope aims to be the lens. A detailed paper on the Data-Scope tells more about what it is: The Data-Scope is a new scientific instrum
sentIndex sentText sentNum sentScore
1 There is a vacuum today in data-intensive scientific computations, similar to the one that lead to the development of the BeoWulf cluster: an inexpensive yet efficient template for data intensive computing in academic environments based on commodity components. [sent-12, score-0.577]
2 Eliminate a lot of system bottlenecks from the storage system by using direct-attached disks, a good balance of disk controllers, ports and drives. [sent-25, score-0.354]
3 It is not hard to build inexpensive servers today where cheap commodity SATA disks can stream over 5GBps per server. [sent-26, score-0.636]
4 Building systems where GPGPUs are co-located with fast local I/O will enable us to stream data onto the GPU cards at multiple GB per second, enabling their stream processing capabilities to be fully utilized. [sent-29, score-0.452]
5 It requires a holistic approach: the data must be first brought to the instrument, then staged, and then moved to the computing nodes that have both enough compute power and enough storage bandwidth (450GBps) to perform the typical analyses, and then the (complex) analyses must be performed. [sent-31, score-0.473]
6 CPU performance has been doubling every 18 months The capacity of disk drives is doubling at a similar rate, somewhat slower that the original Kryder’s Law prediction, driven by higher density platters. [sent-36, score-0.663]
7 The result of this divergence is that while sequential IO speeds increase with density, random IO speeds have changed only moderately. [sent-38, score-0.471]
8 Due to the increasing difference between the sequential and random IO speeds of our disks, only sequential disk access is possible – if a 100TB computational problem requires mostly random access patterns, it cannot be done. [sent-39, score-0.751]
9 Network speeds, even in the data center, are unable to keep up with the doubling of the data sizes. [sent-40, score-0.341]
10 Petabytes of data we cannot move the data where the computing is–instead we must bring the computing to the data. [sent-41, score-0.444]
11 Existing supercomputers are not well suited for data intensive computations either; they maximize CPU cycles, but lack IO bandwidth to the mass storage layer. [sent-42, score-0.714]
12 Moreover, most supercomputers lack disk space adequate to store PB-size datasets over multi-month periods. [sent-43, score-0.416]
13 The data movement and access fees are excessive compared to purchasing physical disks, the IO performance they offer is substantially lower (~20MBps), and the amount of provided disk space is woefully inadequate (e. [sent-45, score-0.456]
14 5x more disk space to allow for data staging and replication to and from the performance layer. [sent-56, score-0.456]
15 In the performance layer we will ensure that the achievable aggregate data throughput remains close to the theoretical maximum, which is equal to the aggregate sequential IO speed of all the disks. [sent-57, score-0.623]
16 Each disk is connected to a separate controller port and we use only 8-port controllers to avoid saturating the controller. [sent-58, score-0.32]
17 We will use the new LSI 9200-series disk controllers, which provide 6Gbps SATA ports and a very high throughput Each performance server will also have four high-speed solid-state disks to be used as an intermediate storage tier for temporary storage and caching for random access patterns. [sent-59, score-0.947]
18 The performance server will use a SuperMicro SC846A chassis, with 24 hot-swap disk bays, four internal SSDs, and two GTX480 Fermi-based NVIDIA graphics cards, with 500 GPU cores each, offering an excellent price-performance for floating point operations at an estimated 3 teraflops per card. [sent-60, score-0.312]
19 To do so we amortize the motherboard and disk controllers among as many disks as possible, using backplanes with SATA expanders while still retaining enough disk bandwidth per server for efficient data replication and recovery tasks. [sent-62, score-1.15]
20 A storage node will consist of 3 SuperMicro SC847 chassis, one holding the motherboard and 36 disks, with the other two holding 45 disks each, for a total of 126 drives with a total storage capacity of 252TB. [sent-65, score-1.006]
wordName wordTfidf (topN-words)
[('disks', 0.311), ('sata', 0.185), ('szalay', 0.185), ('instrument', 0.177), ('disk', 0.172), ('io', 0.15), ('controllers', 0.148), ('sequential', 0.14), ('drives', 0.124), ('speeds', 0.121), ('data', 0.117), ('motherboard', 0.112), ('storage', 0.11), ('inexpensive', 0.108), ('doubling', 0.107), ('intensive', 0.106), ('aggregate', 0.106), ('computing', 0.105), ('maximize', 0.101), ('cards', 0.098), ('supermicro', 0.096), ('roberto', 0.096), ('interview', 0.095), ('consist', 0.093), ('stream', 0.09), ('random', 0.089), ('chassis', 0.089), ('mystery', 0.085), ('space', 0.084), ('performance', 0.083), ('supercomputers', 0.08), ('acquisition', 0.08), ('analyses', 0.08), ('datasets', 0.08), ('law', 0.079), ('suited', 0.075), ('holding', 0.073), ('ports', 0.072), ('gpu', 0.072), ('scientific', 0.071), ('layer', 0.071), ('commodity', 0.07), ('density', 0.07), ('eye', 0.064), ('computations', 0.064), ('bandwidth', 0.061), ('era', 0.059), ('driving', 0.058), ('per', 0.057), ('multicores', 0.056)]
simIndex simValue blogId blogTitle
same-blog 1 0.99999988 1186 high scalability-2012-02-02-The Data-Scope Project - 6PB storage, 500GBytes-sec sequential IO, 20M IOPS, 130TFlops
Introduction: “ Data is everywhere, never be at a single location. Not scalable, not maintainable. ” –Alex Szalay While Galileo played life and death doctrinal games over the mysteries revealed by the telescope, another revolution went unnoticed, the microscope gave up mystery after mystery and nobody yet understood how subversive would be what it revealed. For the first time these new tools of perceptual augmentation allowed humans to peek behind the veil of appearance. A new new eye driving human invention and discovery for hundreds of years. Data is another material that hides, revealing itself only when we look at different scales and investigate its underlying patterns. If the universe is truly made of information , then we are looking into truly primal stuff. A new eye is needed for Data and an ambitious project called Data-scope aims to be the lens. A detailed paper on the Data-Scope tells more about what it is: The Data-Scope is a new scientific instrum
2 0.21046169 1279 high scalability-2012-07-09-Data Replication in NoSQL Databases
Introduction: This is the third guest post ( part 1 , part 2 ) of a series by Greg Lindahl, CTO of blekko, the spam free search engine. Previously, Greg was Founder and Distinguished Engineer at PathScale, at which he was the architect of the InfiniPath low-latency InfiniBand HCA, used to build tightly-coupled supercomputing clusters. blekko's home-grown NoSQL database was designed from the start to support a web-scale search engine, with 1,000s of servers and petabytes of disk. Data replication is a very important part of keeping the database up and serving queries. Like many NoSQL database authors, we decided to keep R=3 copies of each piece of data in the database, and not use RAID to improve reliability. The key goal we were shooting for was a database which degrades gracefully when there are many small failures over time, without needing human intervention. Why don't we like RAID for big NoSQL databases? Most big storage systems use RAID levels like 3, 4, 5, or 10 to improve relia
3 0.17905477 1511 high scalability-2013-09-04-Wide Fast SATA: the Recipe for Hot Performance
Introduction: This is a guest post by Brian Bulkowski , CTO and co-founder of Aerospike , a leading clustered NoSQL database, has worked in the area of high performance commodity systems since 1989. This blog post will tell you exactly how to build a multi-terabyte high throughput datacenter server. A fast, reliable multi-terrabyte data tier can be used for recent behavior (messages, tweets, plays, actions), or anywhere that today you use Redis or Memcache. You need to know: Which SSDs work Which chassis work How to configure your RAID cards Intel’s SATA solutions – combined with a high capacity storage server like the Dell R720xd and a host bus adapter based on the LSI 2208, and a Flash optimized database like Aerospike , enables high throughput and low latency. In a wide configuration, with 12 to 20 drives per 2U server, individual servers can cost-effectively serve at high throughput with 16T at $2.50 per GB with the s3700, or $1.25 with the s3500. Other SSD of
4 0.17812876 1369 high scalability-2012-12-10-Switch your databases to Flash storage. Now. Or you're doing it wrong.
Introduction: This is a guest post by Brian Bulkowski , CTO and co-founder of Aerospike , a leading clustered NoSQL database, has worked in the area of high performance commodity systems since 1989. Why flash rules for databases The economics of flash memory are staggering. If you’re not using SSD, you are doing it wrong. Not quite true, but close. Some small applications fit entirely in memory – less than 100GB – great for in-memory solutions. There’s a place for rotational drives (HDD) in massive streaming analytics and petabytes of data. But for the vast space between, flash has become the only sensible option. For example, the Samsung 840 costs $180 for 250GB. The speed rating for this drive is rated by the manufacturer at 96,000 random 4K read IOPS, and 61,000 random 4K write IOPS. The Samsung 840 is not alone at this price performance. A 300GB Intel 320 is $450. An OCZ Vertex 4 256GB is $235, with the Intel being rated as slowest, but our internal testing showing
5 0.16797122 1114 high scalability-2011-09-13-Must see: 5 Steps to Scaling MongoDB (Or Any DB) in 8 Minutes
Introduction: Jared Rosoff concisely, effectively, entertainingly, and convincingly gives an 8 minute MongoDB tutorial on scaling MongoDB at Scale Out Camp . The ideas aren't just limited to MongoDB, they work for most any database: Optimize your queries; Know your working set size; Tune your file system; Choose the right disks; Shard. Here's an explanation of all 5 strategies: Optimize your queries . Computer science works. Complexity analysis works. A btree search is faster than a table scan. So analyze your queries. Use explain to see what your query is doing. If it is saying it's using a cursor then it's doing a table scan. That's slow. Look at the number of documents it looks at to satisfy a query. Look at how long it takes. Fix: add indexes. It doesn't matter if you are running on 1 or 100 servers. Know your working set size . Sticking memcache in front of your database is silly. You have lots of RAM, use it. Embed your cache in the database, which is how MongoDB works. Working set
6 0.16390681 538 high scalability-2009-03-16-Are Cloud Based Memory Architectures the Next Big Thing?
7 0.16235997 1291 high scalability-2012-07-25-Vertical Scaling Ascendant - How are SSDs Changing Architectures?
8 0.15640819 182 high scalability-2007-12-12-Oracle Can Do Read-Write Splitting Too
11 0.13950638 666 high scalability-2009-07-30-Learn How to Think at Scale
12 0.13764393 920 high scalability-2010-10-15-Troubles with Sharding - What can we learn from the Foursquare Incident?
13 0.13675296 1475 high scalability-2013-06-13-Busting 4 Modern Hardware Myths - Are Memory, HDDs, and SSDs Really Random Access?
14 0.13063604 1066 high scalability-2011-06-22-It's the Fraking IOPS - 1 SSD is 44,000 IOPS, Hard Drive is 180
15 0.12955754 1316 high scalability-2012-09-04-Changing Architectures: New Datacenter Networks Will Set Your Code and Data Free
16 0.12486412 786 high scalability-2010-03-02-Using the Ambient Cloud as an Application Runtime
17 0.12035613 112 high scalability-2007-10-04-You Can Now Store All Your Stuff on Your Own Google Like File System
18 0.12024236 1207 high scalability-2012-03-12-Google: Taming the Long Latency Tail - When More Machines Equals Worse Results
19 0.11947776 274 high scalability-2008-03-12-YouTube Architecture
20 0.11884687 589 high scalability-2009-05-05-Drop ACID and Think About Data
topicId topicWeight
[(0, 0.23), (1, 0.104), (2, 0.025), (3, 0.052), (4, -0.075), (5, 0.081), (6, 0.068), (7, 0.001), (8, -0.005), (9, 0.052), (10, 0.042), (11, -0.098), (12, 0.022), (13, 0.079), (14, 0.024), (15, 0.084), (16, -0.014), (17, 0.022), (18, -0.06), (19, 0.062), (20, -0.026), (21, 0.059), (22, -0.008), (23, 0.028), (24, -0.019), (25, -0.044), (26, -0.017), (27, -0.07), (28, -0.071), (29, 0.041), (30, 0.015), (31, -0.01), (32, 0.058), (33, 0.025), (34, -0.028), (35, 0.009), (36, 0.034), (37, 0.01), (38, -0.009), (39, -0.036), (40, -0.005), (41, -0.05), (42, -0.005), (43, 0.028), (44, 0.001), (45, -0.029), (46, -0.044), (47, -0.084), (48, 0.005), (49, -0.015)]
simIndex simValue blogId blogTitle
same-blog 1 0.96044123 1186 high scalability-2012-02-02-The Data-Scope Project - 6PB storage, 500GBytes-sec sequential IO, 20M IOPS, 130TFlops
Introduction: “ Data is everywhere, never be at a single location. Not scalable, not maintainable. ” –Alex Szalay While Galileo played life and death doctrinal games over the mysteries revealed by the telescope, another revolution went unnoticed, the microscope gave up mystery after mystery and nobody yet understood how subversive would be what it revealed. For the first time these new tools of perceptual augmentation allowed humans to peek behind the veil of appearance. A new new eye driving human invention and discovery for hundreds of years. Data is another material that hides, revealing itself only when we look at different scales and investigate its underlying patterns. If the universe is truly made of information , then we are looking into truly primal stuff. A new eye is needed for Data and an ambitious project called Data-scope aims to be the lens. A detailed paper on the Data-Scope tells more about what it is: The Data-Scope is a new scientific instrum
2 0.85731685 1369 high scalability-2012-12-10-Switch your databases to Flash storage. Now. Or you're doing it wrong.
Introduction: This is a guest post by Brian Bulkowski , CTO and co-founder of Aerospike , a leading clustered NoSQL database, has worked in the area of high performance commodity systems since 1989. Why flash rules for databases The economics of flash memory are staggering. If you’re not using SSD, you are doing it wrong. Not quite true, but close. Some small applications fit entirely in memory – less than 100GB – great for in-memory solutions. There’s a place for rotational drives (HDD) in massive streaming analytics and petabytes of data. But for the vast space between, flash has become the only sensible option. For example, the Samsung 840 costs $180 for 250GB. The speed rating for this drive is rated by the manufacturer at 96,000 random 4K read IOPS, and 61,000 random 4K write IOPS. The Samsung 840 is not alone at this price performance. A 300GB Intel 320 is $450. An OCZ Vertex 4 256GB is $235, with the Intel being rated as slowest, but our internal testing showing
3 0.85197258 1511 high scalability-2013-09-04-Wide Fast SATA: the Recipe for Hot Performance
Introduction: This is a guest post by Brian Bulkowski , CTO and co-founder of Aerospike , a leading clustered NoSQL database, has worked in the area of high performance commodity systems since 1989. This blog post will tell you exactly how to build a multi-terabyte high throughput datacenter server. A fast, reliable multi-terrabyte data tier can be used for recent behavior (messages, tweets, plays, actions), or anywhere that today you use Redis or Memcache. You need to know: Which SSDs work Which chassis work How to configure your RAID cards Intel’s SATA solutions – combined with a high capacity storage server like the Dell R720xd and a host bus adapter based on the LSI 2208, and a Flash optimized database like Aerospike , enables high throughput and low latency. In a wide configuration, with 12 to 20 drives per 2U server, individual servers can cost-effectively serve at high throughput with 16T at $2.50 per GB with the s3700, or $1.25 with the s3500. Other SSD of
4 0.82559377 726 high scalability-2009-10-22-Paper: The Case for RAMClouds: Scalable High-Performance Storage Entirely in DRAM
Introduction: Stanford Info Lab is taking pains to document a direction we've been moving for a while now, using RAM not just as a cache, but as the primary storage medium. Many quality products have built on this model. Even if the vision isn't radical, the paper does produce a lot of data backing up the transition, which is in itself helpful. From the The Abstract: Disk-oriented approaches to online storage are becoming increasingly problematic: they do not scale grace-fully to meet the needs of large-scale Web applications, and improvements in disk capacity have far out-stripped improvements in access latency and bandwidth. This paper argues for a new approach to datacenter storage called RAMCloud, where information is kept entirely in DRAM and large-scale systems are created by aggregating the main memories of thousands of commodity servers. We believe that RAMClouds can provide durable and available storage with 100-1000x the throughput of disk-based systems and 100-1000x lower access lat
5 0.80648863 1035 high scalability-2011-05-05-Paper: A Study of Practical Deduplication
Introduction: With BigData comes BigStorage costs. One way to store less is simply not to store the same data twice . That's the radically simple and powerful notion behind data deduplication . If you are one of those who got a good laugh out of the idea of eliminating SQL queries as a rather obvious scalability strategy, you'll love this one, but it is a powerful feature and one I don't hear talked about outside the enterprise. A parallel idea in programming is the once-and-only-once principle of never duplicating code. Using deduplication technology, for some upfront CPU usage, which is a plentiful resource in many systems that are IO bound anyway, it's possible to reduce storage requirements by upto 20:1, depending on your data, which saves both money and disk write overhead. This comes up because of really good article Robin Harris of StorageMojo wrote, All de-dup works , on a paper, A Study of Practical Deduplication by Dutch Meyer and William Bolosky, For a great explanation o
6 0.80086911 823 high scalability-2010-05-05-How will memristors change everything?
8 0.79642743 1279 high scalability-2012-07-09-Data Replication in NoSQL Databases
10 0.78647417 104 high scalability-2007-10-01-SmugMug Found their Perfect Storage Array
11 0.78425044 1177 high scalability-2012-01-19-Is it time to get rid of the Linux OS model in the cloud?
12 0.77284253 1545 high scalability-2013-11-08-Stuff The Internet Says On Scalability For November 8th, 2013
13 0.7709502 1066 high scalability-2011-06-22-It's the Fraking IOPS - 1 SSD is 44,000 IOPS, Hard Drive is 180
14 0.76967615 901 high scalability-2010-09-16-How Can the Large Hadron Collider Withstand One Petabyte of Data a Second?
15 0.75933957 1483 high scalability-2013-06-27-Paper: XORing Elephants: Novel Erasure Codes for Big Data
16 0.7538684 1291 high scalability-2012-07-25-Vertical Scaling Ascendant - How are SSDs Changing Architectures?
17 0.75283098 526 high scalability-2009-03-05-Strategy: In Cloud Computing Systematically Drive Load to the CPU
18 0.74936527 128 high scalability-2007-10-21-Paper: Standardizing Storage Clusters (with pNFS)
19 0.74935943 1214 high scalability-2012-03-23-Stuff The Internet Says On Scalability For March 23, 2012
20 0.74742746 852 high scalability-2010-07-07-Strategy: Recompute Instead of Remember Big Data
topicId topicWeight
[(1, 0.092), (2, 0.187), (5, 0.014), (10, 0.085), (27, 0.021), (30, 0.02), (38, 0.027), (40, 0.018), (47, 0.021), (48, 0.11), (51, 0.02), (61, 0.091), (77, 0.013), (79, 0.114), (85, 0.052), (94, 0.039)]
simIndex simValue blogId blogTitle
same-blog 1 0.92416549 1186 high scalability-2012-02-02-The Data-Scope Project - 6PB storage, 500GBytes-sec sequential IO, 20M IOPS, 130TFlops
Introduction: “ Data is everywhere, never be at a single location. Not scalable, not maintainable. ” –Alex Szalay While Galileo played life and death doctrinal games over the mysteries revealed by the telescope, another revolution went unnoticed, the microscope gave up mystery after mystery and nobody yet understood how subversive would be what it revealed. For the first time these new tools of perceptual augmentation allowed humans to peek behind the veil of appearance. A new new eye driving human invention and discovery for hundreds of years. Data is another material that hides, revealing itself only when we look at different scales and investigate its underlying patterns. If the universe is truly made of information , then we are looking into truly primal stuff. A new eye is needed for Data and an ambitious project called Data-scope aims to be the lens. A detailed paper on the Data-Scope tells more about what it is: The Data-Scope is a new scientific instrum
2 0.91912746 873 high scalability-2010-08-06-Hot Scalability Links for Aug 6, 2010
Introduction: Twitter Sees Its 20 Billionth Tweet writes Marshall Kirkpatrick of ReadWriteWeb. Startups die for not having customers, so STOP thinking about how to scale . Alessandro Orsi says focusing on the architecture and scaling possibilities of your app for millions of users is just plain dumb...concentrate on marketing...concentrate on user experience . Alessandro is perfectly correct, but this isn't the year the 2000 when the default architecture that is easy is also not scalable and when sites were built from scratch one painful user at a time. Today neither is tue. In the era of social networks, where Facebook has 500 million users, successful applications can and often do spike to millions of users seemingly overnight. And you have to have some architecture. With today's tool-chains you don't have to choose easy and non-scalable. There are other options. Of course, it's all pointless without customers and that is what you need to worry about, but it's a false choice in this era to
3 0.9092195 1612 high scalability-2014-03-14-Stuff The Internet Says On Scalability For March 14th, 2014
Introduction: Hey, it's HighScalability time: LifeExplorer Cells in 3D Quotable Quotes: The Master Switch : History shows a typical progression of information technologies: from somebody’s hobby to somebody’s industry; from jury-rigged contraption to slick production marvel; from a freely accessible channel to one strictly controlled by a single corporation or cartel—from open to closed system. @adrianco : #qconlondon @russmiles on PaaS "As old as I am, a leaky abstraction would be awful..." @Obdurodon : "Scaling is hard. Let's make excuses." @TomRoyce : @jeffjarvis the rot is deep... The New Jersey pols just used Tesla to shake down the car dealers. @CompSciFact : "The cheapest, fastest and most reliable components of a computer system are those that aren't there." -- Gordon Bell @glyph : “Eventually consistent” is just another way to say “not consistent right now”. @nutshell : LinkedIn is shutting down access to their APIs
4 0.90147305 498 high scalability-2009-01-20-Product: Amazon's SimpleDB
Introduction: Update 35 : How and Why Glue is Using Amazon SimpleDB instead of a Relational Database . Discusses a key design decision that required duplicating data in order to mimic RDBMS joins: Given the trade off between potential inconsistencies and scalability, social services have to choose the latter. Update 34 : Apparently Amazon pulled this article. I'm not sure what that means. Maybe time went backwards or something? Amazon dramatically drops SimpleDB pricing to $0.25 per GB per month from $1.50 per GB . This puts SimpleDB on par with Google App Engine . They also announced a few new features: a SQL-like SELECT API as well as a Batch Put operation to streamline uploading of multiple items or attributes . One of the complaints against SimpleDB is that programmers end up writing too much code to do simple things. These features and a much cheaper price should help considerably. And you can store lots of data now. GAE is still capped. Update 33 : Amazon announces
5 0.89984328 610 high scalability-2009-05-29-Is Eucalyptus ready to be your private cloud?
Introduction: Update: : Eucalyptus Goes Commercial with $5.5M Funding Round . This removes my objection that it's an academic project only. Go team go! Rich Wolski , professor of Computer Science at the University of California, Santa Barbara, gave a spirited talk on Eucalyptus to a large group of very interested cloudsters at the Eucalyptus Cloud Meetup . If Rich could teach computer science at every school the state of the computer science industry would be stratospheric. Rich is dynamic, smart, passionate, and visionary. It's that vision that prompted him to create Eucalyptus in the first place. Rich and his group are experts in grid and distributed computing, having a long and glorious history in that space. When he saw cloud computing on the rise he decided the best way to explore it was to implement what everyone accepted as a real cloud, Amazon's API. In a remarkably short time they implement Eucalyptus and have been improving it and tracking Amazon's changes ever since. The question
6 0.89916408 716 high scalability-2009-10-06-Building a Unique Data Warehouse
8 0.89769459 1112 high scalability-2011-09-07-What Google App Engine Price Changes Say About the Future of Web Architecture
9 0.89620048 1291 high scalability-2012-07-25-Vertical Scaling Ascendant - How are SSDs Changing Architectures?
10 0.89533502 1007 high scalability-2011-03-18-Stuff The Internet Says On Scalability For March 18, 2011
11 0.89379454 619 high scalability-2009-06-05-HotPads Shows the True Cost of Hosting on Amazon
12 0.89345372 1491 high scalability-2013-07-15-Ask HS: What's Wrong with Twitter, Why Isn't One Machine Enough?
13 0.89293361 1649 high scalability-2014-05-16-Stuff The Internet Says On Scalability For May 16th, 2014
14 0.89248592 72 high scalability-2007-08-22-Wikimedia architecture
15 0.89182878 1148 high scalability-2011-11-29-DataSift Architecture: Realtime Datamining at 120,000 Tweets Per Second
16 0.89122581 1600 high scalability-2014-02-21-Stuff The Internet Says On Scalability For February 21st, 2014
17 0.89037693 1460 high scalability-2013-05-17-Stuff The Internet Says On Scalability For May 17, 2013
18 0.8889522 628 high scalability-2009-06-13-Neo4j - a Graph Database that Kicks Buttox
19 0.88833326 780 high scalability-2010-02-19-Twitter’s Plan to Analyze 100 Billion Tweets
20 0.88827085 611 high scalability-2009-05-31-Need help on Site loading & database optimization - URGENT