PLATFORM ARCHITECTURE HUB
OpenSearch & Neural Search Architecture
Distributed open-source search, k-NN vector indexing, neural search plugins, shard management, and high-throughput ingestion.
0 Technical Deep-DivesAll Legacy URLs Preserved (HTTP 200)Zero Data Loss
Architectural Context: Building fully open-source, scalable search infrastructure with enterprise-grade security and hybrid lexical-vector retrieval.
✦ OPENSEARCH VS. ANVI SEARCH ARCHITECTURE
OpenSearch vs. Anvi Search Architectural Comparison
OpenSearch provides massive horizontal distributed indexing for log and text search. Anvi Search builds upon this by adding sub-20ms Kafka CDC updates, in-memory Roaring Bitsets for deep commerce facets, and automated Endeca dimension translation.
| Architectural Dimension | OpenSearch | ⚡ Anvi Search | Business Impact |
|---|---|---|---|
| Real-Time Streaming vs. JVM Heap Thrashing | High JVM memory footprint and GC latency spikes during heavy indexing bursts | ✓ Sub-20ms Kafka CDC Streaming with zero-GC memory buffers | Guarantees live inventory and price accuracy during peak retail flash sales. |
| Disjunctive Faceting & Multi-Select Counts | Post-filter aggregations trigger Cartesian index expansions | ✓ In-Memory Roaring Bitsets (sub-2ms facet recalculation across 350k SKUs) | Sub-5ms multi-facet navigation without cluster CPU starvation. |
| Legacy Endeca Migration Parity | Requires months of custom application code and query DSL rewrites | ✓ Automated Dimension Precedence & Record Filter translation engine | Reduces Endeca cutover timelines from 9 months to weeks. |
| Contextual RAG & Hallucination Shield | Requires custom external LangChain/LlamaIndex pipelines | ✓ Built-in Situated Metadata Synthesizer & Verification Shield | Prevents conversational LLM agents from hallucinating out-of-stock items. |