{"id":373,"date":"2026-06-05T14:05:25","date_gmt":"2026-06-05T21:05:25","guid":{"rendered":"https:\/\/www.couchbase.com\/\/?p=373"},"modified":"2026-06-05T14:05:25","modified_gmt":"2026-06-05T21:05:25","slug":"couchbase-vs-mongodb-vector-search-benchmarks","status":"publish","type":"documents","link":"https:\/\/www.couchbase.com\/ja\/document\/couchbase-vs-mongodb-vector-search-benchmarks\/","title":{"rendered":"Couchbase vs. MongoDB: Vector Search Benchmarks"},"content":{"rendered":"<p class=\"wp-block-paragraph\">In the market for a high-performance, cost-efficient database for your AI-powered apps? Vector search is just one of many critical areas where Couchbase\u2019s unified data platform measurably beats MongoDB\u2122. This new vector search benchmark report compares Couchbase 8.0 and MongoDB 8.0 for recall, latency, and throughput using VectorDBBench, the standard benchmarking suite for vector workloads. Couchbase significantly outperformed MongoDB for both standard and large-scale datasets:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>100M vector dataset with 768 dimensions \u2013 Couchbase achieved higher throughput for all recall levels while providing higher levels and lower latencies<\/li>\n\n\n<li>1B vector dataset with 128 dimensions \u2013 Couchbase\u2019s performance degraded only slightly, while MongoDB could no longer achieve any production-grade performance<\/li>\n\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The report includes full details of the testing methodology, hardware setups, and workloads, plus a discussion of the results.<\/p>\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\" style=\"margin-top:var(--wp--preset--spacing--lg)\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/info.couchbase.com\/rs\/302-GJY-034\/images\/COU_1372%20-%208.0%20Benchmarks%20for%20Hyperscale%20Vector%20Search%20-%20WP.pdf\" title=\"\u30ec\u30dd\u30fc\u30c8\u3092\u5165\u624b\u3059\u308b\" target=\"_self\">\u30ec\u30dd\u30fc\u30c8\u3092\u5165\u624b\u3059\u308b<\/a><\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>In the market for a high-performance, cost-efficient database for your AI-powered apps? Vector search is just one of many critical areas where Couchbase\u2019s unified data platform measurably beats MongoDB\u2122. This new vector search benchmark report compares Couchbase 8.0 and MongoDB 8.0 for recall, latency, and throughput using VectorDBBench, the standard benchmarking suite for vector workloads. Couchbase significantly outperformed MongoDB for both standard and large-scale datasets: The report includes full details of the testing methodology, hardware setups, and workloads, plus a discussion of the results.<\/p>","protected":false},"author":15093,"featured_media":0,"menu_order":0,"template":"single-document","meta":{"_acf_changed":false,"inline_featured_image":false,"_acf":"","footnotes":""},"document-tracks":[],"class_list":["post-373","documents","type-documents","status-publish","hentry"],"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>Couchbase vs. MongoDB: Vector Search Benchmarks<\/title>\n<meta name=\"description\" content=\"Download the VectorDBBench results comparing Couchbase and MongoDB vector search at 100M and 1B vectors for throughput, latency, and recall.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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