{"id":66901,"date":"2022-07-14T21:21:52","date_gmt":"2022-07-14T18:21:52","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=66901"},"modified":"2022-07-15T17:36:11","modified_gmt":"2022-07-15T14:36:11","slug":"nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/","title":{"rendered":"NoSQL DBaaS Comparison 2022: Couchbase Capella vs. MongoDB Atlas"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_79_2 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#Exponential_growth_of_real-time_data\" >Exponential growth of real-time data<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#Evaluated_database_systems\" >Evaluated database systems<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#Workload_with_100_reads\" >Workload with 100% reads<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#Pagination_Workload_results\" >Pagination Workload results<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#More_performance_results\" >More performance results?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#Further_reading\" >Further reading<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"Exponential_growth_of_real-time_data\"><\/span>Exponential growth of real-time data<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Each year, the amount of data that high-load apps operate with, such as e-commerce and social networks, is only exponentially growing. According to a <a href=\"https:\/\/www.seagate.com\/files\/www-content\/our-story\/trends\/files\/idc-seagate-dataage-whitepaper.pdf\" rel=\"noopener\" target=\"_blank\">report<\/a> by IDC, the Global Datasphere, the summation of all digital content, which was 33 ZB in 2018 will increase to 175 ZB by 2025. Additionally, real-time data will double in size, reaching 30% by 2025.<\/p>\n<p>To deal with a constant increase of real-time data, modern apps are now utilizing NoSQL solutions. According to a <a href=\"https:\/\/dataintelo.com\/report\/nosql-market\/\" rel=\"noopener\" target=\"_blank\">report<\/a> by Dataintelo, the global NoSQL market, which was valued at $3.2 billion in 2019, is expected to reach $22.08 billion by 2026.<\/p>\n<p>Compared to relational databases, NoSQL systems provide better performance, scalability, and resiliency needed by modern applications. However, these solutions require a significant amount of time and effort to deploy, configure, manage, and support. To offset this cost, many organizations are relying on NoSQL databases as a service (DBaaS) instead. In this manner, they can benefit from improved performance, while also avoiding the necessity to invest increasing amounts of time and money on cluster support, deployment, and maintenance.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/IDC-real-time-global-datasphere-projection-data-age-2025.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/IDC-real-time-global-datasphere-projection-data-age-2025-1024x576.png\" width=\"720\" class=\"aligncenter size-large wp-image-66953\" \/><\/a><small>Real-time data to reach 30% of the Global Datasphere by 2025 (<a href=\"https:\/\/www.seagate.com\/files\/www-content\/our-story\/trends\/files\/idc-seagate-dataage-whitepaper.pdf\" rel=\"noopener\" target=\"_blank\">Image credit<\/a>)<\/small><\/center><\/p>\n<p>Today, we are announcing the results of our latest <a href=\"https:\/\/www.altoros.com\/research-papers\/performance-evaluation-couchbase-capella-vs-mongodb-atlas-2022\/\">research<\/a> that compares the performance of two NoSQL databases as a service: Couchbase Capella (March 2022 release) and MongoDB Atlas v5.0. The evaluation was conducted on three different cluster configurations\u20146, 9, and 18 nodes\u2014as well as under four different workloads.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Evaluated_database_systems\"><\/span>Evaluated database systems<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Couchbase-Capella-logo-300x100.png\" width=\"200\" class=\"alignright size-medium wp-image-66925\" \/><\/p>\n<p><a href=\"https:\/\/www.couchbase.com\/products\/capella\" rel=\"noopener\" target=\"_blank\">Couchbase Capella<\/a> is a fully managed database as a service. It combines features of a key-value store allowing operations on single documents and acts as a schemaless document store to access the data by querying through SQL++ (SQL for JSON documents).<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/mongodb-atlas-logo-300x169.png\" width=\"200\" class=\"alignright size-medium wp-image-66911\" \/><\/p>\n<p><a href=\"https:\/\/www.mongodb.com\/atlas\/database\" rel=\"noopener\" target=\"_blank\">MongoDB Atlas<\/a> is a document-oriented NoSQL database. It has extensive support for a variety of secondary indexes and API-based ad hoc queries, as well as strong features for manipulating JSON documents. The database puts forward a separate and incremental approach to data replication and partitioning that happen as completely independent processes.<\/p>\n<p>To provide verifiable results, the benchmark was performed on Amazon Elastic Compute Cloud (EC2) instances. For consistency, the <a href=\"https:\/\/en.wikipedia.org\/wiki\/YCSB\" rel=\"noopener\" target=\"_blank\">Yahoo! Cloud Serving Benchmark<\/a> (YCSB) was used to evaluate the NoSQL databases.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Couchbase-Capella-MongoDB-Atlas-Q3-2022-YCSB-components.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Couchbase-Capella-MongoDB-Atlas-Q3-2022-YCSB-components-1024x576.png\" width=\"720\" class=\"aligncenter size-large wp-image-66923\" \/><\/a><small>The components of the YCSB client (<a href=\"https:\/\/www.altoros.com\/blog\/performance-evaluation-couchbase-capella-vs-mongodb-atlas-2022\/\">Image credit<\/a>)<\/small><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Workload_with_100_reads\"><\/span>Workload with 100% reads<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>During the evaluation, one of the scenarios conducted was Pagination Workload, which is a query with a single filtering option, an offset, and a limit. This simulates a selection by field with pagination. This scenario is used for listings, such as e-commerce category pages or search engine results. The scenario was executed under the following settings:<\/p>\n<ul>\n<li style=\"margin-bottom: 6px;\">The read ratio was 100%.<\/li>\n<li style=\"margin-bottom: 6px;\">The size of a data set was scaled in accordance with the cluster size: 5 million customers (each 4 KB in size) on a 6-node cluster, 25 million customers on a 9-node cluster, and 100 million customers on an 18-node cluster.<\/li>\n<li style=\"margin-bottom: 6px;\">The maximum of a query length reached 100 records.<\/li>\n<li style=\"margin-bottom: 6px;\">Uniform was used as a query length distribution.<\/li>\n<li style=\"margin-bottom: 6px;\">The maximum query offset reached 5 records.<\/li>\n<li>Uniform was used as a query offset distribution.<\/li>\n<\/ul>\n<p>To speed up query execution on Couchbase Capella, secondary indexes were created for specific fields by which data is filtered. The database provides two index storage modes: memory- and disk-optimized. The latter is the default mode.<\/p>\n<p>Memory-optimized indexes use an in-memory database with a lock-free skip list, which has a probabilistic ordered data structure and, thus, performs at in-memory speeds. Memory-optimized global secondary indexes were created for filtering fields with index replication on each cluster node as shown below.<\/p>\n<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<code style=\"color: black; background-color: #e6e6e6;\">CREATE INDEX `query1` ON `bucket`(`address`.`country`) USING GSI;<\/code><\/p>\n<p>MongoDB Atlas uses mongos instances to route queries and operations to shards in a sharded cluster. If the result of the query is not sorted, the mongos instance opens a result cursor from all cursors on the shards using a round robin method. To improve the performance of the database, an additional secondary index was added to a filtered field as shown below.<\/p>\n<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<code style=\"color: black; background-color: #e6e6e6;\">db.customer.ensureIndex( { \"address.country\": 1 } );<\/code><\/p>\n<p>The following queries were used to perform Pagination Workload.<\/p>\n<table style=\"width: 720px; margin-left: auto; margin-right: auto;\" border=\"1\">\n<tbody>\n<tr style=\"height: 21.5px;\">\n<td style=\"background-color: #cedae8; width: 50%; height: 21.5px;\">\n<div style=\"text-align: center;\"><small><strong>Couchbase SQL++<\/strong><\/small><\/div>\n<\/td>\n<td style=\"background-color: #cedae8; width: 50%; height: 21.5px;\">\n<div style=\"text-align: center;\"><small><strong>MongoDB Query<\/strong><\/small><\/div>\n<\/td>\n<\/tr>\n<tr style=\"height: 46px;\">\n<td style=\"height: 46px;\"><code style=\"color: black; font-size: 16px; background-color: #e6e6e6;\">SELECT meta().id<br \/>\nFROM `bucket`<br \/>\nWHERE address.country='$1'<br \/>\nOFFSET $2<br \/>\nLIMIT $3 <\/code><\/td>\n<td style=\"height: 46px;\"><code style=\"color: black; font-size: 16px; background-color: #e6e6e6;\">db.customer.find({<br \/>\naddress.country: $1<br \/>\n }, {<br \/>\n_id: 1<br \/>\n })<br \/>\n.skip($2)<br \/>\n.limit($3) <\/code><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Pagination_Workload_results\"><\/span>Pagination Workload results<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>On a 6-node cluster, MongoDB Atlas had the lower throughput of 36,392 ops\/sec, while Couchbase Capella had 51,952 ops\/sec. On a 9-node cluster, MongoDB Atlas slightly decreased throughput with a rate of 35,325 ops\/sec. This happened due to the amount of records per shard. On the other hand, Couchbase Capella increased throughput to 60,680 ops\/sec. Couchbase Capella performed best on an 18-node cluster with 65,228 ops\/sec, while MongoDB Atlas managed a throughput of 29,300 ops\/sec.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Couchbase-Capella-MongoDB-Atlas-Q3-2022-Pagination-Workload.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Couchbase-Capella-MongoDB-Atlas-Q3-2022-Pagination-Workload-1024x576.png\" alt=\"\" width=\"720\" class=\"aligncenter size-large wp-image-66919\" \/><\/a><small>Throughput and latency for Pagination Workload (<a href=\"https:\/\/www.altoros.com\/blog\/performance-evaluation-couchbase-capella-vs-mongodb-atlas-2022\/\">Image credit<\/a>)<\/small><\/center><\/p>\n<div id=\"attachment_66961\" style=\"width: 160px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Ivan-Shyrma.png\"><img decoding=\"async\" aria-describedby=\"caption-attachment-66961\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Ivan-Shyrma-150x150.png\" width=\"150\" class=\"size-thumbnail wp-image-66961\" \/><\/a><p id=\"caption-attachment-66961\" class=\"wp-caption-text\"><small>Ivan Shyrma<\/small><\/p><\/div>\n<p>Couchbase Capella demonstrated good results for Pagination Workload, gradually increasing in throughput, as the number of nodes grew. However, latency rose from 3 ms on a 6-node to 6 ms on an 18-node cluster.<\/p>\n<blockquote><p>&#8220;As in previous benchmarks, Couchbase Capella demonstrated better performance than Atlas due to its active-active, all-worker nodes architecture. Capella is also easier to query due to its SQL support. These factors translate to a better price-to-performance ratio in real-world environments.&#8221;<br \/>\n\u2014Ivan Shyrma, Data Engineer, Altoros<\/p><\/blockquote>\n<p>MongoDB Atlas had the inverse result, as the cluster size increased, the performance of the database declined. This is due to the size of the data set and indexes being doubled, while the cluster size increased by only 50%. The latency for MongoDB Atlas also decreased from 11 ms on a 6-node cluster to 12.4 ms on a 9-node cluster and finally 14.4 ms on an 18-node cluster.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"More_performance_results\"><\/span>More performance results?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Check out our full report to learn more about how we configured Couchbase Capella and MongoDB Atlas, as well as how both NoSQL databases performed in the evaluation. In addition to Pagination Workload, the report also compared the DBaaS systems across three other scenarios: update-heavy (50% reads and 50% updates), short-range scan (95% scans and 5% updates), and JOIN (with grouping and ordering applied).<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Couchbase-Capella-MongoDB-Atlas-Q3-2022-preview-NoSQL-DBaaS.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/Couchbase-Capella-MongoDB-Atlas-Q3-2022-preview-NoSQL-DBaaS-1024x461.png\" width=\"720\" class=\"aligncenter size-large wp-image-66908\" \/><\/a><\/center><\/p>\n<p>Download the full report <a href=\"https:\/\/www.altoros.com\/research-papers\/performance-evaluation-couchbase-capella-vs-mongodb-atlas-2022\/\">here<\/a>.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Further_reading\"><\/span>Further reading<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2021-couchbase-capella-vs-azure-cosmos-db\/\">NoSQL DBaaS Comparison 2021: Couchbase Capella vs. Azure Cosmos DB<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/nosql-comparison-2021-couchbase-server-mongodb-and-cassandra-datastax\/\">NoSQL Comparison 2021: Couchbase Server, MongoDB, and Cassandra (DataStax)<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/dbaas-evaluation-couchbase-cloud-mongodb-atlas-and-amazon-dynamodb\/\">DBaaS Evaluation 2020: Couchbase Capella, MongoDB Atlas, and Amazon DynamoDB<\/a><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<hr \/>\n<p><center><small>This blog post was written by <a href=\"https:\/\/www.altoros.com\/blog\/author\/carlo\/\">Carlo Gutierrez<\/a><br \/>\nwith assistance from Ivan Shyrma and <a href=\"https:\/\/www.altoros.com\/blog\/author\/alex\/\">Alex Khizhniak<\/a>.<\/small><\/center><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Exponential growth of real-time data<\/p>\n<p>Each year, the amount of data that high-load apps operate with, such as e-commerce and social networks, is only exponentially growing. According to a report by IDC, the Global Datasphere, the summation of all digital content, which was 33 ZB in 2018 will increase to 175 [&#8230;]<\/p>\n","protected":false},"author":32,"featured_media":66955,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[214],"tags":[894,692,895],"class_list":["post-66901","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tutorials","tag-benchmarking","tag-nosql","tag-research-and-development"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>NoSQL DBaaS Comparison 2022: Couchbase Capella vs. MongoDB Atlas | Altoros<\/title>\n<meta name=\"description\" content=\"Our new report compares the performance of the two systems when running four workloads: update-heavy, short-range scan, pagination, and JOIN.\" \/>\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.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"NoSQL DBaaS Comparison 2022: Couchbase Capella vs. MongoDB Atlas | Altoros\" \/>\n<meta property=\"og:description\" content=\"Exponential growth of real-time data Each year, the amount of data that high-load apps operate with, such as e-commerce and social networks, is only exponentially growing. According to a report by IDC, the Global Datasphere, the summation of all digital content, which was 33 ZB in 2018 will increase to 175 [...]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/\" \/>\n<meta property=\"og:site_name\" content=\"Altoros\" \/>\n<meta property=\"article:published_time\" content=\"2022-07-14T18:21:52+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-07-15T14:36:11+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/NoSQL-DBaaS-evaluation-Q3-2022-Couchbase-Capella-MongoDB-Atlas.gif\" \/>\n\t<meta property=\"og:image:width\" content=\"1280\" \/>\n\t<meta property=\"og:image:height\" content=\"720\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/gif\" \/>\n<meta name=\"author\" content=\"Carlo Gutierrez\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Carlo Gutierrez\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"7 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/\",\"url\":\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/\",\"name\":\"NoSQL DBaaS Comparison 2022: Couchbase Capella vs. MongoDB Atlas | Altoros\",\"isPartOf\":{\"@id\":\"https:\/\/www.altoros.com\/blog\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/NoSQL-DBaaS-evaluation-Q3-2022-Couchbase-Capella-MongoDB-Atlas.gif\",\"datePublished\":\"2022-07-14T18:21:52+00:00\",\"dateModified\":\"2022-07-15T14:36:11+00:00\",\"author\":{\"@id\":\"https:\/\/www.altoros.com\/blog\/#\/schema\/person\/833e109f77de753b2b472dca0236b442\"},\"breadcrumb\":{\"@id\":\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#primaryimage\",\"url\":\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/NoSQL-DBaaS-evaluation-Q3-2022-Couchbase-Capella-MongoDB-Atlas.gif\",\"contentUrl\":\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2022\/07\/NoSQL-DBaaS-evaluation-Q3-2022-Couchbase-Capella-MongoDB-Atlas.gif\",\"width\":1280,\"height\":720},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.altoros.com\/blog\/nosql-dbaas-comparison-2022-couchbase-capella-vs-mongodb-atlas\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.altoros.com\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"NoSQL DBaaS Comparison 2022: Couchbase Capella vs. MongoDB Atlas\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.altoros.com\/blog\/#website\",\"url\":\"https:\/\/www.altoros.com\/blog\/\",\"name\":\"Altoros\",\"description\":\"Insight\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.altoros.com\/blog\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.altoros.com\/blog\/#\/schema\/person\/833e109f77de753b2b472dca0236b442\",\"name\":\"Carlo Gutierrez\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.altoros.com\/blog\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2021\/02\/CG_portrait-2-96x96.jpg\",\"contentUrl\":\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2021\/02\/CG_portrait-2-96x96.jpg\",\"caption\":\"Carlo Gutierrez\"},\"description\":\"Carlo Gutierrez is a Technical Writer at Altoros. 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