{"id":8486,"date":"2021-02-03T14:31:16","date_gmt":"2021-02-03T13:31:16","guid":{"rendered":"https:\/\/blog.capdata.fr\/?p=8486"},"modified":"2021-02-03T14:49:47","modified_gmt":"2021-02-03T13:49:47","slug":"paas-postgresql-aws-vs-azure","status":"publish","type":"post","link":"https:\/\/blog.capdata.fr\/index.php\/paas-postgresql-aws-vs-azure\/","title":{"rendered":"PaaS PostgreSQL AWS vs Azure"},"content":{"rendered":"\"twitter\"<\/a>\"linkedin\"<\/a>\"mail\"<\/a>

Introduction<\/h1>\n

Maintenant que nous avons vu en d\u00e9tail les performances des PaaS PostgreSQL sur AWS puis sur Azure nous allons essayer de comparer ceux-ci ; nous essaierons de construire un jugement objectif, attention cependant, celui-ci est bas\u00e9 sur un benchmark de type TPC-C, il se peut donc que dans certains cas le comportement observ\u00e9 ne soit pas identique, d’autre part, les configurations postgreSQL ont \u00e9t\u00e9 laiss\u00e9es \u00e0 leurs valeurs pr\u00e9d\u00e9finies qui peuvent donc varier d’un “Cloud provider” \u00e0 l’autre.<\/p>\n

Normalisation<\/h1>\n

De fa\u00e7on \u00e0 pouvoir comparer il \u00e0 d’abord fallu “normaliser les PaaS”, c’est \u00e0 dire pouvoir faire correspondre les types d’instances entre les diff\u00e9rents “Cloud Provider”, ainsi les instances de type\u00a0 “GP” (General Purpose) d’Azure correspondent \u00e0 des instances “db.m” d’AWS et les instances “MO”\u00a0 (Memory Optimized) correspondent \u00e0 des instances de type “db.r” (une remarque qui ne change \u00e0 rien au test, ce sont \u00e0 chaque fois des instances de 5eme g\u00e9n\u00e9ration qui sont utilis\u00e9es, c\u00e0d “db.m5” ou “db.r5” pour AWS et Gen 5 chez Azure) :<\/p>\n

Pour les instances GP Azure provisionne 5Go de RAM \/ vCore
\nPour les instances MO Azure provisionne 10Go de RAM \/ vCore<\/p>\n\n<\/colgroup>\n<\/colgroup>\n<\/colgroup>\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
AWS<\/span><\/b><\/td>\n\u00a0<\/span><\/b><\/td>\n\u00a0<\/span><\/b><\/td>\nAZURE<\/span><\/b><\/td>\n\u00a0<\/span><\/b><\/td>\n\u00a0<\/span><\/b><\/td>\n<\/tr>\n
Instance class<\/span><\/b><\/td>\nCPU<\/span><\/b><\/td>\nMEM<\/span><\/b><\/td>\nCLASS<\/span><\/b><\/td>\nCPU<\/span><\/b><\/td>\nMEM<\/span><\/b><\/td>\n<\/tr>\n
db.m5.8xlarge<\/span><\/td>\n32<\/span><\/td>\n128<\/span><\/td>\nGP_32<\/span><\/td>\n32<\/span><\/td>\n160<\/span><\/td>\n<\/tr>\n
db.m5.4xlarge<\/span><\/td>\n16<\/span><\/td>\n64<\/span><\/td>\nGP_16<\/span><\/td>\n16<\/span><\/td>\n80<\/span><\/td>\n<\/tr>\n
db.m5.2xlarge<\/span><\/td>\n8<\/span><\/td>\n32<\/span><\/td>\nGP_8<\/span><\/td>\n8<\/span><\/td>\n40<\/span><\/td>\n<\/tr>\n
db.m5.xlarge<\/span><\/td>\n4<\/span><\/td>\n16<\/span><\/td>\nGP_4<\/span><\/td>\n4<\/span><\/td>\n20<\/span><\/td>\n<\/tr>\n
db.m5.large<\/span><\/td>\n2<\/span><\/td>\n8<\/span><\/td>\nGP_2<\/span><\/td>\n2<\/span><\/td>\n10<\/span><\/td>\n<\/tr>\n
db.r5.8xlarge<\/span><\/td>\n32<\/span><\/td>\n256<\/span><\/td>\nMO_32<\/span><\/td>\n32<\/span><\/td>\n320<\/span><\/td>\n<\/tr>\n
db.r5.4xlarge<\/span><\/td>\n16<\/span><\/td>\n128<\/span><\/td>\nMO_16<\/span><\/td>\n16<\/span><\/td>\n160<\/span><\/td>\n<\/tr>\n
db.r5.2xlarge<\/span><\/td>\n8<\/span><\/td>\n64<\/span><\/td>\nMO_8<\/span><\/td>\n8<\/span><\/td>\n80<\/span><\/td>\n<\/tr>\n
db.r5.xlarge<\/span><\/td>\n4<\/span><\/td>\n32<\/span><\/td>\nMO_4<\/span><\/td>\n4<\/span><\/td>\n40<\/span><\/td>\n<\/tr>\n
db.r5.large<\/span><\/td>\n2<\/span><\/td>\n16<\/span><\/td>\nMO_2<\/span><\/td>\n2<\/span><\/td>\n20<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

On a donc les instances Azure qui sont provisionn\u00e9es avec un peu plus de m\u00e9moire.<\/p>\n

Par souci de commodit\u00e9, dans ce qui suit les d\u00e9nomination d’instances suivantes seront utilis\u00e9es pour AWS et Azure :<\/p>\n

<GP|MO>_<vCPU>_<Stockage> (la quantit\u00e9 de m\u00e9moire allou\u00e9e pourra donc \u00eatre retrouv\u00e9e au besoin dans le tableau ci-dessus.<\/p>\n

Comparaison des performances<\/h1>\n

Nous allons comparer ici AWS (RDS et Aurora) et Azure (Single Server et Flexible Server), Aurora ne pouvant \u00eatre provisionn\u00e9 que sur des instances de type “db.r”, on restreindra le comparatif \u00e0 uniquement des instances de type AWS “db.r” et Azure “MO” ; de plus, \u00e9tant donn\u00e9 que les IOPS ne sont pas une contrainte sur Aurora on utilisera le stockage le plus gros provisionn\u00e9 lors des benchs (2To) comme r\u00e9f\u00e9rence de comparaison et ce m\u00eame si en fait sur Aurora les 2To ne sont pas r\u00e9ellement provisionn\u00e9s (pour rappel, sur Aurora le stockage est de facto en augmentation automatique par incr\u00e9ment de 30Go, cf :\u00a0https:\/\/blog.capdata.fr\/index.php\/aws-rds-aurora-postgresql\/<\/a>).<\/p>\n

\"\"<\/p>\n

Remarque : Le stockage provisionn\u00e9 ici est de 2To !!!<\/span><\/p>\n

Aurora est donc surtout tr\u00e8s performant pour des grosses instances (par rapport aux autre PaaS, je rappelle aussi qu’ici le stockage a \u00e9t\u00e9 sur-dimensionn\u00e9 pour profiter de plus d’IO).
\nRDS classique s’en sort tr\u00e8s bien pour les petites instances.
\nAzure Single Storage est plus performant qu’Azure Flexible Server (toujours avec un stockage sur-dimensionn\u00e9 car avec un stockage normalement dimensionn\u00e9 la tendance est invers\u00e9e).<\/p>\n

Pour rappel sur les comparatifs complets, cf : https:\/\/blog.capdata.fr\/index.php\/azure-et-postgresql-en-paas<\/span>\/<\/a><\/span> et\u00a0 https:\/\/blog.capdata.fr\/index.php\/aws-rds-aurora-postgresql\/<\/a> et ci-dessous les graphes.<\/p>\n

Comparaison performances Azure Single Server vs Flexible Server<\/h2>\n

\"\"<\/p>\n

Comparaison performances AWS RDS vs AWS Aurora<\/h2>\n

\"\"<\/p>\n

Comparaison financi\u00e8re<\/h1>\n

La comparaison financi\u00e8re ci-dessous permet de comparer le “co\u00fbt d’une transaction” entre les diff\u00e9rents PaaS Azure (Single Server et Flexible Server) et AWS (RDS en GP2, RDS en Provisioned IOPS 10k, 30k et Aurora) test\u00e9s pr\u00e9c\u00e9demment.<\/p>\n

La d\u00e9finition de la “taille” (l’instance utilis\u00e9e) est d\u00e9finie comme ci-dessus, c\u00e0d :<\/p>\n

<MO|GP>_<vCore>_<stockage en Mo><\/p>\n

Remarque : Pour AWS MO est \u00e9quivalent aux instances de type db.r5 et GP aux instances de type db.m5<\/em><\/p>\n

R\u00e9sum\u00e9<\/h2>\n

Ci-dessous un comparatif avec une taille de stockage \u00e0 1To, seule capacit\u00e9 o\u00f9 les tests ont tous \u00e9t\u00e9 faits (en effet, pour tester du “provisioned IOPS” sur RDS il faut provisionner une quantit\u00e9 suffisante de stockage).<\/p>\n

 <\/p>\n\n<\/colgroup>\n<\/colgroup>\n<\/colgroup>\n<\/colgroup>\n\n\n\n\n\n\n\n\n
SIZE<\/span><\/td>\n<\/tr>\n
\"Azure\"<\/p>\n

Cost \/ TPM<\/span><\/td>\n

\"aws-logo
\nCost \/ TPM<\/span><\/td>\n<\/tr>\n
Single Server<\/span><\/td>\nFlexible Server<\/span><\/td>\nRDS GP2<\/span><\/td>\nRDS PIO 10k<\/span><\/td>\nRDS PIO 30k<\/span><\/td>\nAurora<\/span><\/td>\n<\/tr>\n
MO_2_1024<\/td>\n0,020<\/td>\n0,025<\/td>\n0,016<\/td>\n0,073<\/td>\n0,250<\/td>\n8,711<\/td>\n<\/tr>\n
MO_4_1024<\/td>\n0,014<\/td>\n0,016<\/td>\n0,020<\/td>\n0,055<\/td>\n0,603<\/td>\n8,407<\/td>\n<\/tr>\n
MO_8_1024<\/td>\n0,011<\/td>\n0,011<\/td>\n0,021<\/td>\n0,045<\/td>\n0,092<\/td>\n11,799<\/td>\n<\/tr>\n
MO_16_1024<\/td>\n0,019<\/td>\n0,018<\/td>\n0,042<\/td>\n0,062<\/td>\n0,108<\/td>\n8,218<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Les co\u00fbts sont exprim\u00e9s en $\/mois\/transaction<\/p>\n

Attention, le tableau ci-dessus peut \u00eatre trompeur, en effet, il ne tient pas compte de l’activit\u00e9 souhait\u00e9e mais fait le postulat que l’on essaie d’avoir le maximum de transactions par minute, ce qui n’est pas souvent le cas.<\/span><\/p>\n

Ainsi, on peut voir \u00e0 quel point Aurora, bien qu’\u00e9tant une solution performante peut vite devenir tr\u00e8s on\u00e9reuse, en effet, dans le calcul du co\u00fbt final \/ TPM a \u00e9t\u00e9 pris en compte le fait que sur Aurora les IOPS sont factur\u00e9es en plus du stockage et de l’instance ; ci-dessous le d\u00e9tail de ces IO.<\/p>\n\n<\/colgroup>\n<\/colgroup>\n\n\n\n\n\n\n\n
PaaS_size<\/td>\nNb IO (75eme percentile)<\/td>\n<\/tr>\n
MO_32<\/td>\n1716014,50994444<\/td>\n<\/tr>\n
MO_8<\/td>\n977871,730525966<\/td>\n<\/tr>\n
MO_4<\/td>\n445554,741155943<\/td>\n<\/tr>\n
MO_2<\/td>\n253022,491465421<\/td>\n<\/tr>\n
MO_16<\/td>\n1813954,3061938<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Remarque, les co\u00fbts inh\u00e9rents au fait de provisionner 10k IOPS et 30k IOPS ont \u00e9galement \u00e9t\u00e9 pris en compte.<\/em><\/p>\n

Tableau complet<\/h2>\n

Et le tableau complet montrant toutes les instances, les TPM et les diff\u00e9rents co\u00fbts.<\/p>\n\n<\/colgroup>\n<\/colgroup>\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
SIZE<\/span><\/td>\n\"Azure\"
\nAzure<\/span><\/td>\n		\"aws-logo
\nAWS<\/span><\/td>\n<\/tr>\n
Costs<\/span><\/td>\nTPM<\/span><\/td>\nCost \/ TPM<\/span><\/td>\nCosts<\/span><\/td>\nTPM<\/span><\/td>\nCost \/ TPM<\/span><\/td>\n<\/tr>\n
Single Server<\/span><\/td>\nFlexible Server<\/span><\/td>\nSingle Server<\/span><\/td>\nFlexible Server<\/span><\/td>\nSingle Server<\/span><\/td>\nFlexible Server<\/span><\/td>\nRDS GP2<\/span><\/td>\nRDS PIO 10k<\/span><\/td>\nRDS PIO 30k<\/span><\/td>\nAurora*<\/span><\/td>\nRDS GP2<\/span><\/td>\nRDS PIO 10k<\/span><\/td>\nRDS PIO 30k<\/span><\/td>\nAurora<\/span><\/td>\nRDS GP2<\/span><\/td>\nRDS PIO 10k<\/span><\/td>\nRDS PIO 30k<\/span><\/td>\nAurora<\/span><\/td>\n<\/tr>\n
GP_2_128<\/td>\n133,00 \u20ac<\/td>\n130,00 \u20ac<\/td>\n1212<\/td>\n10801<\/td>\n0,110 \u20ac<\/td>\n0,012 \u20ac<\/td>\n165,34 \u20ac<\/td>\n1\u00a0325,34 \u20ac<\/td>\n3\u00a0645,34 \u20ac<\/td>\n\u00a0<\/span><\/td>\n11200<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_2_128<\/td>\n175,00 \u20ac<\/td>\n175,00 \u20ac<\/td>\n2029<\/td>\n10011<\/td>\n0,086 \u20ac<\/td>\n0,017 \u20ac<\/td>\n228,70 \u20ac<\/td>\n1\u00a0388,70 \u20ac<\/td>\n3\u00a0708,70 \u20ac<\/td>\n255,28 \u20ac<\/td>\n20901<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n16834<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n9<\/td>\n<\/tr>\n
GP_4_128<\/td>\n251,00 \u20ac<\/td>\n247,00 \u20ac<\/td>\n1779<\/td>\n25339<\/td>\n0,141 \u20ac<\/td>\n0,010 \u20ac<\/td>\n313,66 \u20ac<\/td>\n1\u00a0473,66 \u20ac<\/td>\n3\u00a0793,66 \u20ac<\/td>\n\u00a0<\/span><\/td>\n24066<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_4_128<\/td>\n337,00 \u20ac<\/td>\n337,00 \u20ac<\/td>\n2244<\/td>\n29632<\/td>\n0,150 \u20ac<\/td>\n0,011 \u20ac<\/td>\n440,38 \u20ac<\/td>\n1\u00a0600,38 \u20ac<\/td>\n3\u00a0920,38 \u20ac<\/td>\n496,48 \u20ac<\/td>\n40168<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n30713<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8<\/td>\n<\/tr>\n
GP_8_128<\/td>\n488,00 \u20ac<\/td>\n479,00 \u20ac<\/td>\n2045<\/td>\n41828<\/td>\n0,239 \u20ac<\/td>\n0,011 \u20ac<\/td>\n610,30 \u20ac<\/td>\n1\u00a0770,30 \u20ac<\/td>\n4\u00a0090,30 \u20ac<\/td>\n\u00a0<\/span><\/td>\n42873<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_8_128<\/td>\n660,00 \u20ac<\/td>\n660,00 \u20ac<\/td>\n1824<\/td>\n63373<\/td>\n0,362 \u20ac<\/td>\n0,010 \u20ac<\/td>\n863,74 \u20ac<\/td>\n2\u00a0023,74 \u20ac<\/td>\n4\u00a0343,74 \u20ac<\/td>\n978,88 \u20ac<\/td>\n46677<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n48007<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n12<\/td>\n<\/tr>\n
GP_16_128<\/td>\n963,00 \u20ac<\/td>\n945,00 \u20ac<\/td>\n1619<\/td>\n53316<\/td>\n0,595 \u20ac<\/td>\n0,018 \u20ac<\/td>\n1\u00a0203,58 \u20ac<\/td>\n2\u00a0363,58 \u20ac<\/td>\n4\u00a0683,58 \u20ac<\/td>\n\u00a0<\/span><\/td>\n36851<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_16_128<\/td>\n1\u00a0305,00 \u20ac<\/td>\n1\u00a0306,00 \u20ac<\/td>\n1384<\/td>\n59160<\/td>\n0,943 \u20ac<\/td>\n0,022 \u20ac<\/td>\n1\u00a0710,46 \u20ac<\/td>\n2\u00a0870,46 \u20ac<\/td>\n5\u00a0190,46 \u20ac<\/td>\n1\u00a0943,68 \u20ac<\/td>\n41830<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n127860<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8<\/td>\n<\/tr>\n
GP_2_256<\/td>\n146,00 \u20ac<\/td>\n143,00 \u20ac<\/td>\n2418<\/td>\n12258<\/td>\n0,060 \u20ac<\/td>\n0,012 \u20ac<\/td>\n182,37 \u20ac<\/td>\n1\u00a0342,37 \u20ac<\/td>\n3\u00a0662,37 \u20ac<\/td>\n\u00a0<\/span><\/td>\n11513<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_2_256<\/td>\n188,00 \u20ac<\/td>\n188,00 \u20ac<\/td>\n6519<\/td>\n11774<\/td>\n0,029 \u20ac<\/td>\n0,016 \u20ac<\/td>\n245,73 \u20ac<\/td>\n1\u00a0405,73 \u20ac<\/td>\n3\u00a0725,73 \u20ac<\/td>\n269,36 \u20ac<\/td>\n16377<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n16834<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n9<\/td>\n<\/tr>\n
GP_4_256<\/td>\n264,00 \u20ac<\/td>\n260,00 \u20ac<\/td>\n4793<\/td>\n30607<\/td>\n0,055 \u20ac<\/td>\n0,008 \u20ac<\/td>\n330,69 \u20ac<\/td>\n1\u00a0490,69 \u20ac<\/td>\n3\u00a0810,69 \u20ac<\/td>\n\u00a0<\/span><\/td>\n20136<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_4_256<\/td>\n350,00 \u20ac<\/td>\n350,00 \u20ac<\/td>\n16088<\/td>\n32641<\/td>\n0,022 \u20ac<\/td>\n0,011 \u20ac<\/td>\n457,41 \u20ac<\/td>\n1\u00a0617,41 \u20ac<\/td>\n3\u00a0937,41 \u20ac<\/td>\n510,56 \u20ac<\/td>\n39128<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n30713<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8<\/td>\n<\/tr>\n
GP_8_256<\/td>\n501,00 \u20ac<\/td>\n492,00 \u20ac<\/td>\n7896<\/td>\n60381<\/td>\n0,063 \u20ac<\/td>\n0,008 \u20ac<\/td>\n627,33 \u20ac<\/td>\n1\u00a0787,33 \u20ac<\/td>\n4\u00a0107,33 \u20ac<\/td>\n\u00a0<\/span><\/td>\n47657<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_8_256<\/td>\n673,00 \u20ac<\/td>\n673,00 \u20ac<\/td>\n13657<\/td>\n58740<\/td>\n0,049 \u20ac<\/td>\n0,011 \u20ac<\/td>\n880,77 \u20ac<\/td>\n2\u00a0040,77 \u20ac<\/td>\n4\u00a0360,77 \u20ac<\/td>\n992,96 \u20ac<\/td>\n57498<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n48007<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n12<\/td>\n<\/tr>\n
GP_16_256<\/td>\n976,00 \u20ac<\/td>\n958,00 \u20ac<\/td>\n5559<\/td>\n66177<\/td>\n0,176 \u20ac<\/td>\n0,014 \u20ac<\/td>\n1\u00a0220,61 \u20ac<\/td>\n2\u00a0380,61 \u20ac<\/td>\n4\u00a0700,61 \u20ac<\/td>\n\u00a0<\/span><\/td>\n65691<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_16_256<\/td>\n1\u00a0318,00 \u20ac<\/td>\n1\u00a0319,00 \u20ac<\/td>\n5548<\/td>\n69331<\/td>\n0,238 \u20ac<\/td>\n0,019 \u20ac<\/td>\n1\u00a0727,49 \u20ac<\/td>\n2\u00a0887,49 \u20ac<\/td>\n5\u00a0207,49 \u20ac<\/td>\n1\u00a0957,76 \u20ac<\/td>\n60069<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n127860<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8<\/td>\n<\/tr>\n
GP_2_512<\/td>\n174,00 \u20ac<\/td>\n171,00 \u20ac<\/td>\n4968<\/td>\n9093<\/td>\n0,035 \u20ac<\/td>\n0,019 \u20ac<\/td>\n216,42 \u20ac<\/td>\n1\u00a0376,42 \u20ac<\/td>\n3\u00a0696,42 \u20ac<\/td>\n\u00a0<\/span><\/td>\n19401<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_2_512<\/td>\n216,00 \u20ac<\/td>\n216,00 \u20ac<\/td>\n10479<\/td>\n10450<\/td>\n0,021 \u20ac<\/td>\n0,021 \u20ac<\/td>\n279,78 \u20ac<\/td>\n1\u00a0439,78 \u20ac<\/td>\n3\u00a0759,78 \u20ac<\/td>\n297,52 \u20ac<\/td>\n22901<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n16834<\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n9<\/td>\n<\/tr>\n
GP_4_512<\/td>\n292,00 \u20ac<\/td>\n288,00 \u20ac<\/td>\n9725<\/td>\n23045<\/td>\n0,030 \u20ac<\/td>\n0,012 \u20ac<\/td>\n364,74 \u20ac<\/td>\n1\u00a0524,74 \u20ac<\/td>\n3\u00a0844,74 \u20ac<\/td>\n\u00a0<\/span><\/td>\n29554<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_4_512<\/td>\n378,00 \u20ac<\/td>\n378,00 \u20ac<\/td>\n23090<\/td>\n28656<\/td>\n0,016 \u20ac<\/td>\n0,013 \u20ac<\/td>\n491,46 \u20ac<\/td>\n1\u00a0651,46 \u20ac<\/td>\n3\u00a0971,46 \u20ac<\/td>\n538,72 \u20ac<\/td>\n32332<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n30713<\/td>\n0,015 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8,405 \u20ac<\/td>\n<\/tr>\n
GP_8_512<\/td>\n529,00 \u20ac<\/td>\n520,00 \u20ac<\/td>\n21327<\/td>\n47392<\/td>\n0,025 \u20ac<\/td>\n0,011 \u20ac<\/td>\n661,38 \u20ac<\/td>\n1\u00a0821,38 \u20ac<\/td>\n4\u00a0141,38 \u20ac<\/td>\n\u00a0<\/span><\/td>\n76063<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0,009 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_8_512<\/td>\n701,00 \u20ac<\/td>\n701,00 \u20ac<\/td>\n36539<\/td>\n64192<\/td>\n0,019 \u20ac<\/td>\n0,011 \u20ac<\/td>\n914,82 \u20ac<\/td>\n2\u00a0074,82 \u20ac<\/td>\n4\u00a0394,82 \u20ac<\/td>\n1\u00a0021,12 \u20ac<\/td>\n73817<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n48007<\/td>\n0,012 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n11,798 \u20ac<\/td>\n<\/tr>\n
GP_16_512<\/td>\n1\u00a0004,00 \u20ac<\/td>\n986,00 \u20ac<\/td>\n33032<\/td>\n67148<\/td>\n0,030 \u20ac<\/td>\n0,015 \u20ac<\/td>\n1\u00a0254,66 \u20ac<\/td>\n2\u00a0414,66 \u20ac<\/td>\n4\u00a0734,66 \u20ac<\/td>\n\u00a0<\/span><\/td>\n85698<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0,015 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_16_512<\/td>\n1\u00a0346,00 \u20ac<\/td>\n1\u00a0347,00 \u20ac<\/td>\n26944<\/td>\n73871<\/td>\n0,050 \u20ac<\/td>\n0,018 \u20ac<\/td>\n1\u00a0761,54 \u20ac<\/td>\n2\u00a0921,54 \u20ac<\/td>\n5\u00a0241,54 \u20ac<\/td>\n1\u00a0985,92 \u20ac<\/td>\n78345<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n127860<\/td>\n0,022 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8,218 \u20ac<\/td>\n<\/tr>\n
GP_2_1024<\/td>\n228,00 \u20ac<\/td>\n225,00 \u20ac<\/td>\n7707<\/td>\n10714<\/td>\n0,030 \u20ac<\/td>\n0,021 \u20ac<\/td>\n284,51 \u20ac<\/td>\n1\u00a0444,51 \u20ac<\/td>\n3\u00a0764,51 \u20ac<\/td>\n\u00a0<\/span><\/td>\n19546<\/td>\n20574<\/td>\n22442<\/td>\n#N\/D<\/span><\/td>\n0,015 \u20ac<\/td>\n0,070 \u20ac<\/td>\n0,168 \u20ac<\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_2_1024<\/td>\n270,00 \u20ac<\/td>\n270,00 \u20ac<\/td>\n13245<\/td>\n10805<\/td>\n0,020 \u20ac<\/td>\n0,025 \u20ac<\/td>\n347,87 \u20ac<\/td>\n1\u00a0507,87 \u20ac<\/td>\n3\u00a0827,87 \u20ac<\/td>\n353,84 \u20ac<\/td>\n21780<\/td>\n20587<\/td>\n15313<\/td>\n16834<\/td>\n0,016 \u20ac<\/td>\n0,073 \u20ac<\/td>\n0,250 \u20ac<\/td>\n8,711 \u20ac<\/td>\n<\/tr>\n
GP_4_1024<\/td>\n346,00 \u20ac<\/td>\n342,00 \u20ac<\/td>\n15649<\/td>\n23456<\/td>\n0,022 \u20ac<\/td>\n0,015 \u20ac<\/td>\n432,83 \u20ac<\/td>\n1\u00a0592,83 \u20ac<\/td>\n3\u00a0912,83 \u20ac<\/td>\n\u00a0<\/span><\/td>\n29899<\/td>\n30688<\/td>\n26189<\/td>\n#N\/D<\/span><\/td>\n0,014 \u20ac<\/td>\n0,052 \u20ac<\/td>\n0,149 \u20ac<\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_4_1024<\/td>\n432,00 \u20ac<\/td>\n432,00 \u20ac<\/td>\n30131<\/td>\n26926<\/td>\n0,014 \u20ac<\/td>\n0,016 \u20ac<\/td>\n559,55 \u20ac<\/td>\n1\u00a0719,55 \u20ac<\/td>\n4\u00a0039,55 \u20ac<\/td>\n595,04 \u20ac<\/td>\n28520<\/td>\n31311<\/td>\n6699<\/td>\n30713<\/td>\n0,020 \u20ac<\/td>\n0,055 \u20ac<\/td>\n0,603 \u20ac<\/td>\n8,407 \u20ac<\/td>\n<\/tr>\n
GP_8_1024<\/td>\n583,00 \u20ac<\/td>\n574,00 \u20ac<\/td>\n51375<\/td>\n56428<\/td>\n0,011 \u20ac<\/td>\n0,010 \u20ac<\/td>\n729,47 \u20ac<\/td>\n1\u00a0889,47 \u20ac<\/td>\n4\u00a0209,47 \u20ac<\/td>\n\u00a0<\/span><\/td>\n62496<\/td>\n45416<\/td>\n47342<\/td>\n#N\/D<\/span><\/td>\n0,012 \u20ac<\/td>\n0,042 \u20ac<\/td>\n0,089 \u20ac<\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_8_1024<\/td>\n755,00 \u20ac<\/td>\n755,00 \u20ac<\/td>\n69446<\/td>\n69565<\/td>\n0,011 \u20ac<\/td>\n0,011 \u20ac<\/td>\n982,91 \u20ac<\/td>\n2\u00a0142,91 \u20ac<\/td>\n4\u00a0462,91 \u20ac<\/td>\n1\u00a0077,44 \u20ac<\/td>\n46194<\/td>\n47345<\/td>\n48372<\/td>\n48007<\/td>\n0,021 \u20ac<\/td>\n0,045 \u20ac<\/td>\n0,092 \u20ac<\/td>\n11,799 \u20ac<\/td>\n<\/tr>\n
GP_16_1024<\/td>\n1\u00a0058,00 \u20ac<\/td>\n1\u00a0040,00 \u20ac<\/td>\n77250<\/td>\n73993<\/td>\n0,014 \u20ac<\/td>\n0,014 \u20ac<\/td>\n1\u00a0322,75 \u20ac<\/td>\n2\u00a0482,75 \u20ac<\/td>\n4\u00a0802,75 \u20ac<\/td>\n\u00a0<\/span><\/td>\n74894<\/td>\n46458<\/td>\n52959<\/td>\n#N\/D<\/span><\/td>\n0,018 \u20ac<\/td>\n0,053 \u20ac<\/td>\n0,091 \u20ac<\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_16_1024<\/td>\n1\u00a0400,00 \u20ac<\/td>\n1\u00a0401,00 \u20ac<\/td>\n72340<\/td>\n77191<\/td>\n0,019 \u20ac<\/td>\n0,018 \u20ac<\/td>\n1\u00a0829,63 \u20ac<\/td>\n2\u00a0989,63 \u20ac<\/td>\n5\u00a0309,63 \u20ac<\/td>\n2\u00a0042,24 \u20ac<\/td>\n43456<\/td>\n47841<\/td>\n49108<\/td>\n127860<\/td>\n0,042 \u20ac<\/td>\n0,062 \u20ac<\/td>\n0,108 \u20ac<\/td>\n8,218 \u20ac<\/td>\n<\/tr>\n
GP_2_2048<\/td>\n337,00 \u20ac<\/td>\n334,00 \u20ac<\/td>\n9585<\/td>\n6621<\/td>\n0,035 \u20ac<\/td>\n0,050 \u20ac<\/td>\n420,70 \u20ac<\/td>\n1\u00a0580,70 \u20ac<\/td>\n3\u00a0900,70 \u20ac<\/td>\n\u00a0<\/span><\/td>\n22540<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0,019 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_2_2048<\/td>\n379,00 \u20ac<\/td>\n379,00 \u20ac<\/td>\n11120<\/td>\n8331<\/td>\n0,034 \u20ac<\/td>\n0,045 \u20ac<\/td>\n484,06 \u20ac<\/td>\n1\u00a0644,06 \u20ac<\/td>\n3\u00a0964,06 \u20ac<\/td>\n466,48 \u20ac<\/td>\n20761<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n16834<\/td>\n0,023 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8,718 \u20ac<\/td>\n<\/tr>\n
GP_4_2048<\/td>\n455,00 \u20ac<\/td>\n451,00 \u20ac<\/td>\n24501<\/td>\n20609<\/td>\n0,019 \u20ac<\/td>\n0,022 \u20ac<\/td>\n569,02 \u20ac<\/td>\n1\u00a0729,02 \u20ac<\/td>\n4\u00a0049,02 \u20ac<\/td>\n\u00a0<\/span><\/td>\n42415<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0,013 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_4_2048<\/td>\n541,00 \u20ac<\/td>\n541,00 \u20ac<\/td>\n37207<\/td>\n24624<\/td>\n0,015 \u20ac<\/td>\n0,022 \u20ac<\/td>\n695,74 \u20ac<\/td>\n1\u00a0855,74 \u20ac<\/td>\n4\u00a0175,74 \u20ac<\/td>\n707,68 \u20ac<\/td>\n44550<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n30713<\/td>\n0,016 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8,410 \u20ac<\/td>\n<\/tr>\n
GP_8_2048<\/td>\n692,00 \u20ac<\/td>\n683,00 \u20ac<\/td>\n62430<\/td>\n54995<\/td>\n0,011 \u20ac<\/td>\n0,012 \u20ac<\/td>\n865,66 \u20ac<\/td>\n2\u00a0025,66 \u20ac<\/td>\n4\u00a0345,66 \u20ac<\/td>\n\u00a0<\/span><\/td>\n68180<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0,013 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_8_2048<\/td>\n864,00 \u20ac<\/td>\n864,00 \u20ac<\/td>\n74070<\/td>\n67194<\/td>\n0,012 \u20ac<\/td>\n0,013 \u20ac<\/td>\n1\u00a0119,10 \u20ac<\/td>\n2\u00a0279,10 \u20ac<\/td>\n4\u00a0599,10 \u20ac<\/td>\n1\u00a0190,08 \u20ac<\/td>\n70506<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n48007<\/td>\n0,016 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n11,801 \u20ac<\/td>\n<\/tr>\n
GP_16_2048<\/td>\n1\u00a0167,00 \u20ac<\/td>\n1\u00a0149,00 \u20ac<\/td>\n58392<\/td>\n71574<\/td>\n0,020 \u20ac<\/td>\n0,016 \u20ac<\/td>\n1\u00a0458,94 \u20ac<\/td>\n2\u00a0618,94 \u20ac<\/td>\n4\u00a0938,94 \u20ac<\/td>\n\u00a0<\/span><\/td>\n72923<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n0,020 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n<\/tr>\n
MO_16_2048<\/td>\n1\u00a0509,00 \u20ac<\/td>\n1\u00a0510,00 \u20ac<\/td>\n74289<\/td>\n67449<\/td>\n0,020 \u20ac<\/td>\n0,022 \u20ac<\/td>\n1\u00a0965,82 \u20ac<\/td>\n3\u00a0125,82 \u20ac<\/td>\n5\u00a0445,82 \u20ac<\/td>\n2\u00a0154,88 \u20ac<\/td>\n76100<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n127860<\/td>\n0,026 \u20ac<\/td>\n#N\/D<\/span><\/td>\n#N\/D<\/span><\/td>\n8,219 \u20ac<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

*Co\u00fbts Aurora : Sont exclu ici les co\u00fbts inh\u00e9rents aux IOPS qui sont \u00e0 rajouter \u00e0 la facture globale (0.00000022 \/ IO mensuelle)<\/em><\/p>\n

Comparatif TPM \/ Co\u00fbt<\/h3>\n

Stockage 128Mo<\/h4>\n

\"\"<\/p>\n

Stockage 256Mo<\/h4>\n

\"\"<\/p>\n

Stockage 512Mo<\/h4>\n

\"\"<\/p>\n

Stockage 1024Mo<\/h4>\n

\"\"<\/p>\n

Stockage 2048Mo<\/h4>\n

\"\"<\/p>\n

*Co\u00fbts Aurora : Sont exclu ici les co\u00fbts inh\u00e9rents aux IOPS qui sont \u00e0 rajouter \u00e0 la facture globale (0.00000022 \/ IO mensuelle)<\/em><\/p>\n

Conclusion<\/h1>\n

Ce comparatif aura montr\u00e9 d’une part que bien qu’Aurora soit un PaaS tr\u00e8s performant qui de prime abord peut paraitre peu on\u00e9reux (si on ne prend que le prix de base instance + stockage) ce prix peut vite devenir important en fonction des op\u00e9rations (et donc des IO) lanc\u00e9es sur celui-ci, on le r\u00e9servera donc \u00e0 des besoins sp\u00e9cifiques bien calibr\u00e9s.<\/p>\n

D’autre part, Azure bien qu’assez r\u00e9cent dans le domaine des PaaS PostgreSQL se montre un tr\u00e8s bon challenger face \u00e0 AWS avec des tarifications assez agressives et des performances plus qu’acceptables notamment sur les instances de type Flexible Server (performances \u00e0 rev\u00e9rifier lors de la disponibilit\u00e9 en “General Availability” tout de m\u00eame).<\/p>\n\"twitter\"<\/a>\"linkedin\"<\/a>\"mail\"<\/a>","protected":false},"excerpt":{"rendered":"

Introduction Maintenant que nous avons vu en d\u00e9tail les performances des PaaS PostgreSQL sur AWS puis sur Azure nous allons essayer de comparer ceux-ci ; nous essaierons de construire un jugement objectif, attention cependant, celui-ci est bas\u00e9 sur un benchmark… Continuer la lecture →<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":8534,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[295,282,1,266],"tags":[315],"class_list":["post-8486","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-aws","category-azure","category-non-classe","category-postgresql","tag-paas"],"yoast_head":"\nPaaS PostgreSQL AWS vs Azure - Capdata TECH BLOG<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blog.capdata.fr\/index.php\/paas-postgresql-aws-vs-azure\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PaaS PostgreSQL AWS vs Azure - 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