Real-time vs. offline indexing performance
Real-time indexing adds vectors to the index as they arrive, keeping search up to date with low latency from write to searchability. Offline (batch) indexing builds or rebuilds the index in bulk, often yielding better recall and build performance at the cost of delay until new data is searchable.
Summary
- Real-time indexing: vectors added as they arrive; search stays up to date, low latency from write to searchability. Offline (batch): index built or rebuilt in bulk; often better recall and build performance at the cost of delay until new data is searchable.
- Real-time uses incremental or append-friendly structures; offline can use parallel construction, tune efConstruction, achieve higher recall. Many VDBs use hybrid: real-time buffer for recent data plus periodically merged batch-built indexes. See streaming ingestion.
- Benchmark: indexing throughput (vectors/sec) and time-to-searchable (real-time); total build time and resulting recall (offline). Choice depends on freshness needs and throughput. Pipeline: real-time = insert, incremental update, searchable; offline = bulk build, merge. Practical tip: use hybrid (real-time buffer + periodic batch) for most production workloads.
Real-time vs. batch trade-offs
Real-time systems use incremental or append-friendly structures; updates can slightly degrade graph quality or require periodic compaction. Offline builds can run parallel construction, tune efConstruction and clustering without worrying about write latency, and achieve higher recall for the same memory. Many production VDBs use a hybrid: a real-time buffer or small index for recent data, plus periodically merged batch-built indexes for the bulk of the dataset.
Benchmarking
When benchmarking, measure both indexing throughput (vectors/second) and time-to-searchable for real-time, and total build time and resulting recall for offline. Choice depends on how fresh results must be and whether you can tolerate streaming vs. batch ingestion.
Pipeline: real-time = insert, incremental update, searchable; offline = bulk build, merge. Practical tip: use hybrid (real-time buffer + periodic batch) for most production workloads.
Frequently Asked Questions
What is real-time vs. offline indexing?
Real-time: vectors added as they arrive; search stays up to date with low latency from write to searchability. Offline (batch): index built or rebuilt in bulk; often better recall and build performance but delay until new data is searchable. See incremental building.
When to use real-time indexing?
When results must be fresh (e.g. live dashboards, recent content). Uses incremental or append-friendly structures; updates can slightly degrade graph quality or require periodic compaction. See streaming ingestion.
When to use offline (batch) indexing?
When you can tolerate delay and want maximum recall and build performance. Offline can run parallel construction, tune efConstruction without write-latency concerns.
What is a hybrid approach?
Many production VDBs use a real-time buffer or small index for recent data, plus periodically merged batch-built indexes for the bulk. Balances freshness and recall. See distributed index building.