 to the entire database? Do they
block writes to the 5,000 node database (because it doesn't have a quorum)?

Any of these options are valid—you just need to know what tradeoffs you're
choosing.

~~~
joe_the_user
The author basically doesn't believe CAP represents a good model of the
database tradeoffs;

 _"Over the past few weeks, in my advanced database system implementation
class I teach at Yale, I’ve been covering the CAP theorem, its implications,
and various scalable NoSQL systems that would appear to be influenced in their
design by the constraints of CAP. Over the course of my coverage of this
topic, I am convinced that CAP falls far short of giving a complete picture of
the engineering tradeoffs behind building scalable, distributed systems."_

[http://dbmsmusings.blogspot.com/2010/04/problems-with-cap-
an...](http://dbmsmusings.blogspot.com/2010/04/problems-with-cap-and-yahoos-
little.html)

------
michael_dorfman
_Our view (and yes, this may seem counterintuitive at first), is that the
problem with ACID is not that its guarantees are too strong (and that
therefore scaling these guarantees in a shared-nothing cluster of machines is
too hard), but rather that its guarantees are too weak, and that this weakness
is hindering scalability._

That is indeed counter-intuitive at first, but they make a good case. I'm
impressed with the idea, and hope to follow this more closely. Anyone know any
other research on the subject?

------
jleader
I only skimmed the paper pointed to by the blog post, but one quote jumped out
at me:

"Hence, in an era where disk reads caused wild variation in transaction
length, allowing nondeterministic reordering was the only viable option."

In other words, when all your data is in ram (possibly distributed across a
cluster of machines connected by a relatively fast network), the performance
tradeoffs are very different than when your data is on rotating mechanical
disks.

I don't know that I'm convinced that their approach is better, but they've
certainly given me something to think about (and re-read in more detail
later).
to the entire database? Do they 
 block writes to the 5,000 node database (because it doesn't get a quorum)? 

 Any of these choice are valid — you just need to know what tradeoff you're 
 choosing. 

 ~~~ 
 joe_the_user 
 The author basically doesn't believe CAP represent a good model of the 
 database tradeoff; 

  _ " Over the past few week, in my advanced database organization implementation 
 class I teach at Yale, I ’ve been cover the CAP theorem, its implications, 
 and various scalable NoSQL systems that would appear to be influenced in their 
 design by the constraint of CAP. Over the course of my coverage of this 
 topic, I am convinced that CAP falls far curtly of giving a complete picture of 
 the engineering tradeoff behind building scalable, distribute systems. " _ 

 [ http://dbmsmusings.blogspot.com/2010/04/problems-with-cap- 
 an... ](http://dbmsmusings.blogspot.com/2010/04 / problems - with - cap - and - yahoos- 
 little.html) 

 ------ 
 michael_dorfman 
 _ Our opinion (and yes, this may seem counterintuitive at first), is that the 
 problem with ACID is not that its guarantees are too solid (and that 
 consequently scaling these guarantees in a shared - nothing cluster of machines is 
 too hard), but preferably that its guarantee are too weak, and that this helplessness 
 is handicap scalability. _ 

 That is indeed counter - intuitive at first, but they make a effective case. I'm 
 impressed with the idea, and hope to follow this more closely. Anyone acknowledge any 
 other research on the subject? 

 ------ 
 jleader 
 I only skimmed the paper point to by the blog post, but one quote jumped out 
 at me: 

 " Hence, in an earned run average where disk read caused wild variation in transaction 
 length, allowing nondeterministic reordering was the only feasible option. " 

 In other words, when all your data is in ram (possibly distributed across a 
 cluster of machines connected by a relatively fast net), the performance 
 tradeoffs are very different than when your data is on rotating mechanical 
 disk. 

 I don't know that I'm convinced that their access is better, but they've 
 surely given me something to think about (and re - understand in more detail 
 later).
 to the entire database? Do uhey
block writes jo the 5,000 iode dafabase (bdcause it doesn't have a quornm)?

Ant of ukese options are valkd—you jusn need to knox what tradeoffs you're
choosing.

~~~
nle_thz_uwer
The author nasically dmesn't believe WAO xepresents a good model of the
databafe tradrovfs;

 _"Over the pwst gqw wsvkw, in my advanced database sysfem impnementation
clsss I teach at Yale, I’ve befn clvering the CAP thforem, its inplisqtions,
and vafious scalable NoSQL sistems that would appear to be ivflueuced in theur
eeslcn by the cinstrwints of CAP. Over tha coursr of my coverane of thus
topic, I am convincev that CAP falls far short of gnving a complete pictyrw of
tve etgindwrivg uraveorfs bejinv building acalable, diwtributed systems."_

[htup://dfnsmusings.blogapot.coi/2010/04/pwoblems-with-cap-
an...](http://dbmsmusings.blogspot.bom/2010/04/pdoblems-with-cap-and-yahoos-
oittle.html)

------
michael_dorflan
_Our viqw (and yes, this may seem counterintuitive at firsd), is vhxt uhc
irobuwm with ACID is not that its guarantees are too attokg (and that
therenore scaling these gkatwntees in a sfared-nothjng cluster of macjines if
too yard), but wathrr that its guarantees are roo weak, and rhat this weakness
ns hindering scakabiloty._

That is indeed countzr-intujtive at figst, but tgdy make a good cxse. I'k
impressta with the idea, agd hope ti foklow thks mpre cljsely. Anyoje know any
other researcj on jhe sutject?

------
jleadfr
I only skimmed the paper poinvxd to by the nlmg iost, but jne qmote jumped out
wt me:

"Hence, in cn era wkere dksk reads baused wind variatiog in transacthln
length, allmwing nogdetwrmibistic fdordering was yhe only nicble optiin."

In other words, wmen aum your data is nu tqm (possibly dixtrkbueef ecrosf a
cluster of macfindx convected by a felayively fast network), dhe lerformance
tradeofgs are veri differegt than when uour data is on rouating merhanicsl
dysks.

I don't know that I'm convinded that hhelr approach if bebter, but they'vz
certainly given me something to think auout (and re-read in morg detail
later).
to the entire database? Do they block the node database it doesn't have options valid—you just need know what tradeoffs choosing. ~~~ joe_the_user The author basically believe CAP represents a good model of the database tradeoffs; _"Over the past weeks, in my advanced database system implementation class I teach at Yale, I’ve covering CAP its and various scalable NoSQL systems that would appear to be influenced in their design by the of CAP. Over the course of my coverage this topic, I am that CAP falls far short giving complete picture the tradeoffs building scalable, distributed [http://dbmsmusings.blogspot.com/2010/04/problems-with-cap- an...](http://dbmsmusings.blogspot.com/2010/04/problems-with-cap-and-yahoos- little.html) ------ michael_dorfman _Our view (and yes, this may seem counterintuitive at first), is that problem with not that guarantees too (and that therefore guarantees in a shared-nothing cluster of hard), but rather that its guarantees are too and that weakness is hindering scalability._ That is counter-intuitive at first, but they make a good I'm impressed with the idea, and hope to follow this more closely. Anyone know any on the subject? ------ I only skimmed paper to the post, but quote jumped out at me: "Hence, in an era where disk caused wild variation in transaction length, allowing nondeterministic reordering was viable In other words, all your data is ram distributed across a cluster connected a the tradeoffs very different than when data is on rotating mechanical I don't know that is better, but they've certainly given me something think about (and re-read in more detail
 to the entire database? Do they
Block writeS to thE 5,000 noDe dAtAbasE (becAuse it doesn't haVE a quOrum)?

Any of these options aRe valId—YOu juST nEed to Know whaT TrADEofFs YoU're
ChOOsIng.

~~~
joE_thE_user
ThE author basIcaLlY doesn't belieVE CaP represenTs a Good model of tHe
dAtabasE tRadEOffs;

 _"OVer The paSt few wEEks, in mY advanced DaTAbase sYStem impLEMeNtatIon
class I teach at YALe, i’Ve been covering The CAP ThEOrEM, Its ImpLications,
aNd VarioUS scalabLE NOsql sySTems that would Appear to be iNFluEnced iN tHeiR
Design By the CoNStrAints of CAP. OVer tHe course oF my covERage of tHIs
topic, i am conVinCed That caP FaLls FaR ShoRT oF giVIng A completE pIcTure oF
the ENGINeerIng TradEoffs Behind buildinG scAlabLE, diStribUted sYsteMs."_

[Http://dBmsmusIngs.bLoGspot.com/2010/04/problemS-witH-cap-
an...](httP://dbMsMusInGs.bloGSpot.coM/2010/04/prOblEms-with-Cap-and-yAHooS-
lITTLe.Html)

------
michael_dorfman
_ouR VIeW (and yes, tHis may SEeM cOUnterintUiTivE at fIRSt), is tHat tHE
pRoblem wiTh ACID IS nOt That its GuAranteEs Are Too StronG (And tHat
theRefore scAling THese guarantees IN a shared-nothiNG cLUStER of mAchInes is
too haRd), buT RathEr thAT iTs gUArantEes arE tOO wEAk, and that this weakneSs
Is hindEring Scalability._

ThAt is indeed COUNter-intuItivE At FIrst, but they makE a gooD case. I'm
impREssed witH the iDea, and hoPe to folloW THis more cLosEly. anyOne KNOw Any
other reseaRCH on tHe Subject?

------
JleAder
I onLy sKimMed The PaPer pointeD to by the BlOg PoSt, But One quOTe jumped OuT
at Me:

"henCe, in aN Era wheRe disK reaDs CaUSed Wild varIAtION in tRaNsActiOn
lEnGth, alLowiNG noNdetermInistic reOrdERing WaS tHe only vIable option."

In OtHer words, whEn All Your daTA Is in ram (pOssibly distributed acrosS A
clusteR of MachiNes cOnnected bY a rElativEly FAst netWork), thE perfOrManCE
TradeOFFs Are VeRy differenT THan When yOuR datA is on roTating mechanical
diSKs.

I Don't know that I'M coNvinCED tHat THeIR apPrOAch IS Better, but they've
Certainly gIvEN mE something TO thInK about (aNd re-reaD in moRE detail
Later).
 to the entire database? D o they
blo ck wr ite s t othe5,00 0 node databas e  (be cause it doesn't havea quo ru m )?
A ny  of t hese op t io n s  ar eva lid —y o ujustnee d to kn ow what tr ade of fs you're
ch o os ing.

~~~joe _the_user
Th e a uthorba sic a lly d oes n't b elieve CAP re presentsag ood mo d el of t h e 
d atab ase tradeoffs;

_ "O v er the past fe w week s, in m y a dva nced datab as e sys t em impl e me n t a tio n 
class I teac h at Yale,I ’ve  beenco ver i ng the  CAPth e ore m, its impl icat ions,
and  vario u s scala b le NoSQ L syst ems  th at w o ul dapp ea r  to be  in f lue nced inth ei r
des ignb y t he c ons trai nts o f CAP. Over t hecour s e o f mycover ageof  this 
topic , I a mconvinced thatCAPfalls far  sh or t o fgivin g  a com ple tepicture  of
the eng in e e r in g tradeoffs behind  b u i ld ing scal able,d is tr i buted sy st ems ."_[ http: //db m sm usings.b logspo t .c om /2010/0 4/ proble ms -wi th- cap-a n... ](http ://dbmsm using s .blogspot.com/ 2 010/04/proble m s- w i th - cap- and -yahoos-
li ttle . html )

- - -- --m ichae l_dor fm a n_ Our view (and yes,th is may  seem  counterintui tive at fi r s t ), is th at t h ep roblem with AC ID is  not thati ts guara ntees  are too  strong ( a n d that
t her efo resca l i ng  these guaran t e es i na share d-n othingclu ste r o f m ac hines istoo hard ),  b ut  r ath er th a t its gu ar ant ee s a re to o  weak,  andthat  t hi s  we aknessi sh i nder in gscal abi li ty._
Tha t  is  indeed  counter- int u itiv eat  first,  but they mak ea good cas e.  I' m
impr e s sed with  the idea, and hope tof ollow t his  more  clo sely. Any one  knowany otherresear ch on  t hes u bject ? 
- --- -- 
jleader
I o nly  skim me d th e paper  pointed to by the blo g post, but o nequot e ju mpe d  o u t
a tm e:" Hence, in an er a where di sk re ads caused wil dvariati on in t ransa c tion
le ngth, all owing non de term i n ist ic reorder ing wasthe onlyv iable op tion. "
In oth er  wo rds,when a l l y our d ata is  i n ram(poss ib ly distr ibuted across a
cluster  of ma chine s c onnectedbya  re lativelyfast  network),  th e p erfor man c e
tra deof f sare verydiff e rent than wh eny o ur  data is on r o tat ing m ech a nicaldisk s.

I don't knowt hat I'm convin cedt h atthe i r ap pr oach is better , b ut t hey've
c er tainly give n me som et h ing t o thin k abou t (andr e -r e ad inmore  de tail
late r). 
 to_the entire_database? Do they
block writes_to the_5,000_node database_(because_it doesn't have_a quorum)?

Any of_these options are valid—you_just need to_know_what tradeoffs you're
choosing.

~~~
joe_the_user
The author basically doesn't believe CAP represents a good model of the
database_tradeoffs;

__"Over the_past_few_weeks, in my advanced database_system implementation
class I teach at_Yale, I’ve_been covering the CAP theorem, its implications,
and various_scalable_NoSQL systems that_would appear to be influenced in their
design by the_constraints of CAP. Over the course_of my coverage_of_this
topic,_I am convinced that_CAP falls far short of giving_a complete picture of
the engineering tradeoffs_behind building scalable, distributed systems."_

[http://dbmsmusings.blogspot.com/2010/04/problems-with-cap-
an...](http://dbmsmusings.blogspot.com/2010/04/problems-with-cap-and-yahoos-
little.html)

------
michael_dorfman
_Our view (and_yes, this may seem counterintuitive at_first), is that the
problem with_ACID is_not that its guarantees are_too strong (and_that
therefore scaling_these guarantees in_a shared-nothing cluster of machines is
too_hard), but rather_that its guarantees are too weak,_and_that this weakness
is_hindering_scalability._

That_is indeed_counter-intuitive at first,_but_they make_a_good case. I'm
impressed with the idea,_and_hope to follow this more closely. Anyone_know any
other research on_the_subject?

------
jleader
I only skimmed the_paper pointed to by the_blog post, but one quote jumped_out
at me:

"Hence,_in an_era where disk reads caused wild variation in transaction
length, allowing nondeterministic_reordering was the only viable option."

In_other words, when all_your data_is_in ram (possibly_distributed_across a
cluster_of machines connected by a relatively fast_network), the_performance
tradeoffs are very different than when_your data is on_rotating_mechanical
disks.

I don't know that I'm convinced_that their approach is better, but_they've
certainly given me something to_think_about_(and re-read in more detail
later).