BENCHMARKS
Performance, Scale, and Competitive Comparisons
See the latest evidence for why the most trusted companies in the world rely on our Operational Data Platform for AI®.
OUR DIFFERENCE
AI-first, built to scale
Couchbase was built for the most mission-critical enterprise workloads.
Couchbase ran the open source VectorDBBench benchmark against MongoDB Atlas on equivalent hardware. At 1 billion vectors and each database’s highest recall, Couchbase delivered 703 queries per second to MongoDB’s 2, which is approximately 350x the throughput. The full configuration is published so you can reproduce it.
Altoros used the Yahoo! Cloud Serving Benchmark (YCSB) to compare Couchbase Capella, MongoDB Atlas, Amazon DynamoDB, and Redis Enterprise Cloud across four workloads and four cluster sizes. Capella led on update-heavy and paginated query workloads at every cluster size. Redis led the read-only workload, with Capella second.
benchANT, an independent firm, runs YCSB against SQL and NoSQL databases using vendor defaults and publishes the raw data. As of September 2026, Couchbase holds the #1 throughput result and 5 of the top 10 in its General Purpose workload. On identical three-node AWS clusters, Couchbase delivered 3.9x the throughput versus a popular document store.
Why Couchbase wins in the agentic era
Converged data platform
Natively JSON, SQL, key-value, cache, search, vector, analytics, Agent Memory & MCP Server. One governed copy of data, no ETL, no bolt-ons.
Scales for mission critical
Active-active cross data center replication (XDCR) lets every region take writes. Hyperscale vector indexes reach 1 billion+ vectors beyond memory limits.
Built for machine speed
~3,000x the vector throughput (when tuned for speed), and significantly lower latency compared to MongoDB, with 150x lower query latency for SQL-on-JSON.
Data and AI TCO leadership
Rakuten handles 15 billion call and message events per day with 60% fewer servers.
Hybrid and edge flexibility
Run across cloud, data center, mobile, and edge, with on-device vector and Kubernetes deployment.
AI economics
40%+
fewer LLM calls with semantic caching
33%-45%
less token usage with Agent Memory
100%
tokens eliminated with AI on device
70%
smaller prompts with vector search
COMPARISON
See how we stack up
Benchmarks show how a database performs. Comparisons show how it fits. See how Couchbase stacks up against other cloud NoSQL databases on architecture, features, and cost, so you can choose the platform that fits your workloads.
Compare Couchbase
MongoDB
Compare Couchbase vs. MongoDB™ in performance and scalability.
Oracle
Learn how switching to Couchbase can improve performance, increase flexibility, and reduce costs.
Firebase
See why Couchbase Mobile is preferred for always-on apps that keep working offline and sync when they reconnect.
Apache CouchDB®
Discover how Couchbase differs in terms of capabilities, performance, and support.
DynamoDB
Read why customers switch for performance, price, ease of use, and versatility.
HISTÓRIAS DE CLIENTES
Hear it from customers
You’ve heard our take. Now hear it from those who live it.
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HEALTHCARE
“We get more features, save time, and spend less all at once.”
500%
melhoria no desempenho da consulta
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ENTERTAINMENT
“Couchbase provides sub-millisecond response, which helps ensure an enjoyable experience for users.”
1M
transações por segundo
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MEDIA
“We put data to work in a more efficient way, and we’ve built a strong foundation for the future.”
80%
change management improvement
Couchbase benchmarks FAQ
Independent benchmark reports and comparisons raise common questions. Find answers to the most frequent ones below.
In benchANT’s independent YCSB tests on identical clusters, Couchbase delivered 3.9x MongoDB’s throughput. In Couchbase-run VectorDBBench tests at 1 billion vectors, it delivered 350x.
Three design choices: a memory-first engine with the cache built in, multi-dimensional scaling so each service scales on its own, and every node handling reads and writes for its share of data.
YCSB results from benchANT’s independent ranking and a 2023 Altoros study, plus Couchbase-run VectorDBBench vector search tests with the full configuration published so anyone can reproduce them.
Yes. Vector search powers RAG and AI agents. At 1 billion vectors, Couchbase kept average latency under 100 ms at every accuracy setting tested, with recall up to 93%.
VectorDBBench is an open-source vector search benchmark created by Zilliz. It measures throughput, recall, and latency. Couchbase tested it against MongoDB Atlas at 100M and 1B vectors.
Keep exploring
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The AI Data Plane is changing what’s possible
Agent memory, governed tool access, and MCP, all on one platform.
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Billion-scale vector benchmark results
See how Couchbase and MongoDB compare on vector search throughput, recall, and latency at 1 billion vectors.
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Intrigued? Start today.
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