Qdrant刚发了博客回应Elastic的测试，发现对方没开它的优化功能，一开就反超了：吞吐量翻倍，延迟减半，计算资源只要三分之一。想选向量数据库的可以看看。
Elastic的基准测试声称Qdrant 1.18.1在磁盘搜索上慢7倍，但Qdrant指出测试未开启其两项磁盘优化功能。开启优化后，Qdrant实现2倍吞吐量、一半延迟和1/3计算资源消耗。测试在K8s网络附加存储上进行，Elasticsearch 9.4.1使用DiskBBQ算法，Qdrant 1.18.1。Elastic延迟120-150ms，Qdrant在开启优化后延迟更低。
Elastic's benchmark claims Qdrant is 7x slower on disk search. They never enabled the two features b...
Elastic's benchmark claims Qdrant is 7x slower on disk search. They never enabled the two features built for that workload. We turned them on and found 2x throughput, half the latency, 1/3 the compute. Read more: qdrant.tech/blog/benchmark… Elastic @elastic 7x higher vector search throughput at comparable recall. Elasticsearch 9.4.1 DiskBBQ vs Qdrant 1.18.1, tested on network-attached persistent storage. The storage topology most K8s and managed-cloud deployments actually run on. Not local NVMe. The gap is disk access. DiskBBQ searches a compact quantized index and limits full-precision reads. Qdrant rescores against original vectors on disk. On network-attached storage, those random reads get expensive. Elasticsearch latency: 120 to 150ms across recall levels. Qdrant: 315ms to 900ms as recall increases. Benchmark tool, dataset, and configs are all published below. 🔗 View Quoted Tweet 💬 2 🔄 2 ❤️ 8 👀 591 📊 4 ⚡