{"id":312,"date":"2015-05-28T18:53:03","date_gmt":"2015-05-28T18:53:03","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/couchbase-server-hits-1m-writes-with-3b-items-with-50-nodes-on-google-cloud\/"},"modified":"2015-05-28T18:53:03","modified_gmt":"2015-05-28T18:53:03","slug":"couchbase-server-hits-1m-writes-with-3b-items-with-50-nodes-on-google-cloud","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/pt\/couchbase-server-hits-1m-writes-with-3b-items-with-50-nodes-on-google-cloud\/","title":{"rendered":"Couchbase Server hits 1M writes\/sec with 3B items with 50 nodes on Google Cloud"},"content":{"rendered":"<h1 class=\"wp-block-heading\">High Performance with Couchbase Server on Google Cloud<\/h1>\n\n\n\n<p class=\"wp-block-paragraph\">Couchbase Server is an open source, multi-model NoSQL distributed database that incorporates a JSON document database and key-value store. Couchbase Server is built on a memory-centric architecture designed to deliver consistent high performance, availability, and scalability for enterprise web, mobile, and Internet of Things applications. Couchbase Server also does very well on Google Compute Engine, offering superior price\/performance. Google posted a set of results on Google Cloud blog post\u00a0<a href=\"https:\/\/googlecloudplatform.blogspot.com\/2015\/05\/Couchbase-Server-Hits-One-Million-Writes-Per-Second-with-Just-50-Nodes-of-Google-Compute-Engine.html\">here<\/a>\u00a0and in this post I&#8217;d like to take you through the full set of test runs we have done on the platform.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Over the last year, technology partners have been reporting some exciting performance stats on Google Compute Engine, with <a href=\"https:\/\/googlecloudplatform.blogspot.com\/2014\/03\/cassandra-hits-one-million-writes-per-second-on-google-compute-engine.html\"><u>Cassandra<\/u><\/a> able to sustain 1 million writes per second. We took that as a challenge, and decided to see how much further we could push the scale, and drive down price\/performance. This paper details the results from our experimentations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Before I dive in, I want to thank David Haikney (Couchbase) and Dave Rigby (Couchbase) for all work they have done on the benchmark measurements and Ivan Santa Maria Filho (Google) for all the guidance he provided.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Summary<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Couchbase Server was able to sustain 1.1 million writes per second. The data set size was 3 billion items with a value size of 200 bytes. Pure write workloads are not the only type of workload that is interesting in database but is a challenging one. Number of customers developing IoT (internet of things) applications are faced with a similar challenge. The results of the test prove that Couchbase Server on Google Cloud Platform can be a great fit for IoT apps writing data with high velocity at high volumes.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Benchmark Details<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In our journey, we have tried 2 main benchmark configurations.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Benchmark A:<\/strong> this benchmark configuration operated over 3B items. This measurement simulated the configuration published on <a href=\"https:\/\/googlecloudplatform.blogspot.com\/2014\/03\/cassandra-hits-one-million-writes-per-second-on-google-compute-engine.html\"><u>Cassandra on Google Cloud<\/u><\/a>.<\/li>\n\n\n<li><strong>Benchmark B: <\/strong>This second measurement was done on a smaller data set of 100M items. This measurement simulated the configuration published by <a href=\"https:\/\/googlecloudplatform.blogspot.com\/2014\/12\/aerospike-hits-one-million-writes-Per-Second-with-just-50-Nodes-on-Google-Compute-Engine.html\"><u>Aerospike on Google Cloud<\/u><\/a>.\u200b<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Before I plunge into more details, you can try these benchmarks\u00a0out yourself, or simply look through the scripts for more details. Here is our\u00a0<a href=\"https:\/\/github.com\/couchbaselabs\/google_compute_benchmark\">github repo<\/a>.<\/p>\n\n\n\n<h1 class=\"wp-block-heading\">Benchmark A:<\/h1>\n\n\n\n<h2 class=\"wp-block-heading\">1.1M writes\/sec over 3B Items with 50 nodes (n1-standard-16)<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>1.1M writes\/sec with 3B total items<\/li>\n\n\n<li>Median latency was 15ms<\/li>\n\n\n<li>95th% latency was 27ms.<\/li>\n\n\n<li>The total cost of running the benchmark for an hour is $56.3\/hr.<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Graph below shows the warmup and the sustained writes over time reaching 1.1M.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><img decoding=\"async\" src=\"https:\/\/www.couchbase.com\/wp-content\/uploads\/sites\/5\/2026\/05\/benchmarkafig1.png\" align=\"middle\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Graph below plots the median and 95% latency during the test run<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><img decoding=\"async\" src=\"https:\/\/www.couchbase.com\/wp-content\/uploads\/sites\/5\/2026\/05\/benchmarkafig2.png\" align=\"middle\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Base Data-Set and Bucket Configuration <\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Workload operated on 3 billion total items<\/li>\n\n\n<li>Each item has exactly 200 bytes value.<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Couchbase Server Configuration: <\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Debian was the OS of choice for this run (Debian Wheezy Backports).<\/li>\n\n\n<li>Cluster Configuration\n<ul>\n<li>Server RAM Quota was set to 50GB<\/li>\n<li>Disk queue capacity was set to 5M items<\/li>\n<li>IO Threads were at 4 writer and 1 reader thread<\/li>\n<\/ul>\n<\/li>\n\n\n<li>Bucket Configuration:\n<ul>\n<li>All 3B items were configured to reside in a single bucket.<\/li>\n<li>2 copies of the data was maintained on 2 separate nodes for redundancy. Bucket configuration specified 1 replica in addition to the master copy.<\/li>\n<li>Bucket eviction policy was set to \u201cvalue eviction\u201d<\/li>\n<li>Bucket RAM Quota was set to 50GB per node.<\/li>\n<li>Compaction was disabled<\/li>\n<\/ul>\n<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Virtual Machine Configuration<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>VM Count:<\/strong> 50<\/li>\n\n\n<li><strong>VM Size:<\/strong> n1-standard-16<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">There were many options to pick from on the VM sizes. However we have found the n1-standard-16 with 16 cores to be a great fit for optimal price performance. The test was run with 50, n1-standard-16 VM with a total of 60GB RAM on each node.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Storage: <\/strong>500GB SSD Persistent Disks<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Google Cloud storage performed great under Couchbase Server. We used non-ephemeral, persisted storage option to make this a realistic deployment for production loads. The most optimal throughput with Couchbase Server was achieved with the SSD Persistent Disk offering. Couchbase Server used 500GB SSD <a href=\"https:\/\/cloud.google.com\/compute\/docs\/disks\/\"><u>Persistent Disk<\/u><\/a> as the data volume. Couchbase Server did not use the 10GB root volume for database operations. Journaling was disabled (noatime) on data volume.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Cost per Node:<\/strong> $1.12 \/ hr.<\/li>\n\n\n<li><strong>Total Cost with 50 nodes: <\/strong>$56.30 \/ hr<\/li>\n\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Workload Properties and the Added Durability with \u201cReplicateTo\u201d flag<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The load was generated using pillowfight tool. To provide the added durability guarantee, pillowfight tool was modified to add the \u201cReplicateTo\u201d flag to each write. The option ensures that writes are acknowledged only after the write operation reaches both copies of the data maintained by Couchbase Server.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Couchbase Server uses an active master replica for all of its writes and maintains secondary replicas for redundancy. Couchbase Server comes with a powerful built in replication technology named DCP (database change protocol). DCP streams changes to secondary replicas. Couchbase can maintain sub-millisecond latencies in its default write model with its efficient in memory cache. However the replicated write provides the firm durability under a node failure and ensure no data is lost in case of a failover.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Load Generation Configuration:<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For load generation was done using 32 clients with n1-highcpu-8 VMs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Following was the command line option used for the run 1 client instance with pillowfight<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">.\/cbc-pillowfight &#8211;min-size=200 &#8211;max-size=200 &#8211;num-threads=2 &#8211;num-items=93750000 &#8211;set-pct=100 &#8211;spec=couchbase:\/\/cb-server-1\/charlie &#8211;batch-size=50 &#8211;num-cycles=468750000 &#8211;sequential &#8211;no-population &#8211;rate-limit=20000 &#8211;tokens=275 &#8211;durability<\/p>\n\n\n\n<h1 class=\"wp-block-heading\">Benchmark B:<\/h1>\n\n\n\n<h2 class=\"wp-block-heading\">1M writes\/sec over 100 million Items with 40 nodes (n1-standard-8)<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>1M writes\/sec with 100M total items<\/li>\n\n\n<li>Median latency was 18ms<\/li>\n\n\n<li>95th% latency was 36ms.<\/li>\n\n\n<li>The total cost of running the benchmark for an hour is $21.28\/hr.<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Base Data-Set and Bucket Configuration <\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Workload operated on 100 million total items<\/li>\n\n\n<li>Each item has exactly 200 bytes value.<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Couchbase Server Configuration: <\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Debian was the OS of choice for this run (Debian Wheezy Backports).<\/li>\n\n\n<li>Cluster Configuration\n<ul>\n<li>Server RAM Quota was set to 24GB<\/li>\n<li>Disk queue capacity was set to 5M items<\/li>\n<li>IO Threads were at 2 writer and 1 reader thread<\/li>\n<\/ul>\n<\/li>\n\n\n<li>Bucket Configuration:\n<ul>\n<li>All 100M items were configured to reside in a single bucket.<\/li>\n<li>2 copies of the data was maintained on 2 separate nodes for redundancy. Bucket configuration specified 1 replica in addition to the master copy.<\/li>\n<li>Bucket eviction policy was set to \u201cvalue eviction\u201d<\/li>\n<li>Bucket RAM Quota was set to 24GB per node.<\/li>\n<li>Compaction was disabled<\/li>\n<\/ul>\n<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Virtual Machine Configuration<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>VM Count: 40<\/li>\n\n\n<li>VM Size: n1-standard-8<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">For this smaller item count, we have found the n1-standard-8 with 8 cores to be the best fit for optimal price performance. The test was run with 40x n1-standard-8 VM with a total of 30GB RAM on each node.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Storage: 500GB Standard Persistent Disk<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Google Cloud storage performed great under Couchbase Server. We used non-ephemeral, persisted storage option to make this a realistic deployment for production loads. Optimal price\/performance with Couchbase Server was achieved with the Standard Persistent Disk offering. Couchbase Server used 500GB <a href=\"https:\/\/cloud.google.com\/compute\/docs\/disks\/\"><u>Persistent Disk<\/u><\/a> as the data volume. Couchbase Server did not use the 10GB root volume for database operations. Journaling was disabled (noatime) on data volume.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Cost per node: $0.53 \/ hr.<\/li>\n\n\n<li>Total Cost with 40 nodes: $21.28 \/ hr<\/li>\n\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Workload Properties and the Added Durability with \u201cReplicateTo\u201d flag<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The load was generated using pillowfight tool. To provide the added durability guarantee, pillowfight tool was modified to add the \u201cReplicateTo\u201d flag to each write. The option ensures that writes are acknowledged only after the write operation reaches both copies of the data maintained by Couchbase Server.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Couchbase Server uses an active master replica for all of its writes and maintains secondary replicas for redundancy. Couchbase Server comes with a powerful built in replication technology named DCP (database change protocol). DCP streams changes to secondary replicas. Couchbase can maintain sub-millisecond latencies in its default write model with its efficient in memory cache. However the replicated write provides the firm durability under a node failure and ensure no data is lost in case of a failover.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Load Generation Configuration:<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For load generation was done using 32 clients with n1-highcpu-8 VMs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Following was the command line option used for the run 1 client instance with pillowfight<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">.\/cbc-pillowfight &#8211;min-size=200 &#8211;max-size=200 &#8211;num-threads=2 &#8211;num-items=93750000 &#8211;set-pct=100 &#8211;spec=couchbase:\/\/cb-server-1\/charlie &#8211;batch-size=50 &#8211;num-cycles=468750000 &#8211;sequential &#8211;no-population &#8211;rate-limit=20000 &#8211;tokens=275 &#8211;durability<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">1M writes\/sec is an impressive amount of writes and many of you may never hit this kind of throughput in your systems but it is comforting to know that you can do this 1M writes\/sec over 3B items in as few as\u00a050 nodes in Google Cloud with 6x better price\/performance compared to Cassandra with fully replicated writes!<\/p>","protected":false},"excerpt":{"rendered":"<p>High Performance with Couchbase Server on Google Cloud Couchbase Server is an open source, multi-model NoSQL distributed database that incorporates a JSON document database and key-value store. Couchbase Server is built on a memory-centric architecture designed to deliver consistent high performance, availability, and scalability for enterprise web, mobile, and Internet of Things applications. Couchbase Server [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":18,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"_acf":"","footnotes":""},"categories":[1],"tags":[],"ppma_author":[8],"class_list":["post-312","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.6 (Yoast SEO v27.6) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>High Performance with Couchbase Server on Google Cloud<\/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:\/\/www.couchbase.com\/blog\/pt\/couchbase-server-hits-1m-writes-with-3b-items-with-50-nodes-on-google-cloud\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Couchbase Server hits 1M writes\/sec with 3B items with 50 nodes on Google Cloud\" \/>\n<meta property=\"og:description\" content=\"High Performance with Couchbase Server on Google Cloud Couchbase Server is an open source, multi-model NoSQL distributed database that incorporates a JSON document database and key-value store. Couchbase Server is built on a memory-centric architecture designed to deliver consistent high performance, availability, and scalability for enterprise web, mobile, and Internet of Things applications. Couchbase Server [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.couchbase.com\/blog\/pt\/couchbase-server-hits-1m-writes-with-3b-items-with-50-nodes-on-google-cloud\/\" \/>\n<meta property=\"og:site_name\" content=\"The Couchbase Blog\" \/>\n<meta property=\"article:published_time\" content=\"2015-05-28T18:53:03+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/5\/2026\/05\/couchbase-nosql-dbaas.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1800\" \/>\n\t<meta property=\"og:image:height\" content=\"630\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Cihan Biyikoglu, Director of Product Management, Couchbase\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Cihan Biyikoglu, Director of Product Management, Couchbase\" 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