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Vector Data Migration

Vector Data Migration

2
posts
2025–2026

Qdrant introduces a beta Vector Data Migration Tool designed to simplify moving data between different Qdrant instances and from other vector database providers. This tool streams vectors in live batches, supporting migrations between open source and Qdrant Cloud, or between cloud regions. It allows for changes in collection configuration, such as replication factor or quantization method, during migration. The tool can be run as a container on any machine with connectivity to both source and target. Bazaarvoice successfully migrated billions of vectors from PostgreSQL to Qdrant, achieving a ~100x reduction in storage footprint and sub-100ms query latency with ~98% recall, demonstrating the effectiveness of Qdrant's quantization and multitenancy features for large-scale data migration and operational efficiency.

2026

How Bazaarvoice scaled AI-powered product insights with Qdrant - Qdrant

2/10/2026

Bazaarvoice details their successful migration of billions of vectors from PostgreSQL with pgvector to Qdrant. Key technical challenges and solutions included: scaling to billions of embeddings with cost-efficiency, implementing tenant isolation via payload-based partitioning for scoped searches, and leveraging Qdrant's quantization for significant storage and RAM reduction (~100x). The migration was performed under real-world constraints with streaming data ingestion and disk-backed collections, still achieving sub-100ms query latency and ~98% recall. This migration enabled new product development by removing operational overhead of manual partitioning and enabling flexible, cross-product queries at query time.

2025

Vector Data Migration Tool - Qdrant

6/16/2025

Launch of a beta Vector Data Migration Tool that streams vectors from a source collection to a target Qdrant instance in live batches. Supports migration between Qdrant deployments (open source to cloud, cloud to cloud) and from other vector databases. Enables changing collection configurations like replication factor and quantization method during migration. The tool runs as a container and does not require direct connectivity between source and target databases.