Qdrant Horizontal Scaling

作者 qdrant6a03d0ce8f55无许可证收录于 2026年10月8日更新于 2026年10月8日

Diagnoses and guides Qdrant horizontal scaling decisions. Use when someone asks 'vertical or horizontal?', 'how many nodes?', 'how many shards?', 'how to add nodes', 'resharding', 'data doesn't fit', or 'need more capacity'. Also use when data growth outpaces current deployment.

仅含说明DevOps & Cloud
AI 生成的概览

指导 Qdrant 横向扩展决策:节点数、分片数、副本因子以及重新分片的取舍。

功能
该技能为 Qdrant 向量数据库的容量规划提供咨询式指导。它说明何时应纵向扩展、何时应横向扩展,推荐以三个节点、三个分片、副本因子为二的基线分布式配置,并给出三到六个节点集群的分片数量建议。它还说明何时适合重新分片、其限制以及应避免的做法。
适用场景
当有人询问应纵向还是横向扩展、应使用多少节点或分片、如何添加节点或如何重新分片时使用。当数据增长超出当前 Qdrant 部署的承载能力或需要更多容量时也适用。
运行要求
不需要脚本或工具,仅为说明性指导。应用这些建议需已有 Qdrant 部署;由于自托管部署不支持重新分片,重新分片相关指导适用于 Qdrant Cloud。

What to Do When Qdrant Needs More Capacity

Vertical first: simpler operations, no network overhead, good up to ~100M vectors per node depending on dimensions and quantization. Horizontal when: data exceeds single node capacity, need fault tolerance, need to isolate tenants, or IOPS-bound (more nodes = more independent IOPS).

Most basic distributed configuration

  • 3 nodes, 3 shards with replication_factor: 2 for zero-downtime scaling

Minimum of 3 nodes is important for consensus and fault tolerance. With 3 nodes, you can lose 1 node without downtime. With 2 nodes, losing 1 node causes downtime for collection operations. Replication factor of 2 means each shard has 1 replica, so you have 2 copies of data. This allows for zero-downtime scaling and maintenance. With replication_factor: 1, zero-downtime is not guaranteed even for point-level operations, and cluster maintenance requires downtime.

Choosing number of shards

Shards are the unit of data distribution. More shards allows more nodes and better distribution, but adds overhead. Fewer shards reduces overhead but limits horizontal scaling.

For cluster of 3-6 nodes the recommended shard count is 6-12. This allows for 2-4 shards per node, which balances distribution and overhead.

Changing number of shards

Use when: shard count isn't evenly divisible by node count, causing uneven distribution, or need to rebalance.

Resharding is expensive and time-consuming, it should be used as a last resort if regular data distribution is not possible. Resharding is designed to be transparent for user operations, updates and searches should still work during resharding with some small performance impact.

But resharding operation itself is time-consuming and requires to move large amounts of data between nodes.

  • Available in Qdrant Cloud Resharding
  • Resharding is not available for self-hosted deployments.

Better alternatives: over-provision shards initially, or spin up new cluster with correct config and migrate data.

What NOT to Do

  • Do not jump to horizontal before exhausting vertical (adds complexity for no gain)
  • Do not set shard_number that isn't a multiple of node count (uneven distribution)
  • Do not use replication_factor: 1 in production if you need fault tolerance
  • Do not add nodes without rebalancing shards (use shard move API to redistribute)
  • Do not scale down RAM without load testing (cache eviction causes days-long latency incidents)
  • Do not hit the collection limit by using one collection per tenant (use payload partitioning)

来源与署名

来源:qdrant/skills位于skills/qdrant-scaling/scaling-data-volume/horizontal-scaling提交6a03d0c

许可证: 无许可证

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