5-Lens Empirical Quadrants, Pareto Frontier & 17-Facet AI Catalog
Replaces subjective analyst pay-to-play quadrants with reproducible telemetry across LLMs, CPU/Edge SLMs, 3D/Multimodal, Time-Series Foundation Models (Chronos-Bolt, TimesFM 2.0, Moirai-MoE, TimeGPT, PatchTST, Toto), Agent SDKs/Orchestrators, 7-Stage RAG, DSPy, Embeddings, MCP + A2A, Security, Tracing vs Evaluation, Memory Policies vs Vector/SQL Substrates, and Durable Execution.
All 17 Facets (15) agent_development_orchestration ai_security_and_guardrails automation_ipaas_dag_durable embeddings_and_rerankers evaluation_and_regression_testing llm_frontier_cloud llm_open_weights_cloud memory_behavior_policies multimodal_vision_audio_3d observability_tracing_monitoring programmatic_prompt_workflow_optimization protocols_mcp_and_a2a rag_context_pipeline slm_cpu_edge_quantized teleon_team_simulation_provenance timeseries_foundation_models vector_and_transactional_storage
5 Orthogonal Ranking Lenses
- Lens 1 (Empirical 2x2 Quadrant): X = Verified Execution Reliability vs Y = Architectural Composability and Governance Fit.
- Lens 2 (Constraint-Weighted Wave): Custom workload weights plus Tversky hard vetoes (
spdx_license, blast class, CPU-only). - Lens 3 (Exact Pareto Frontier): Non-dominated set across Quality, Latency, Cost, Cliff Retention, and Lock-in Freedom (orange nodes).
- Lens 4 (Jagged-Frontier Cliff Index): Perturbed neighbor retention ratio.
- Lens 5 (Team Marginal Value / WAR): Paired holdout lift net of coordination token tax.
| Component & Publisher | Primary Facet | Quadrant & Frontier | Lens Scores | Cliff & WAR | License |
|---|---|---|---|---|---|
| TigerBeetle TigerBeetle ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER PARETO | Exec: 99, Fit: 96, Wave: 96.74 | Cliff: 98%, WAR: +0.33 | Apache-2.0 |
| PostgreSQL + pgvector / pgvectorscale PostgreSQL / Timescale ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER PARETO | Exec: 97, Fit: 95, Wave: 96.04 | Cliff: 95%, WAR: +0.32 | PostgreSQL |
| DuckDB + VSS / Parquet DuckDB Labs ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 98, Fit: 95, Wave: 95.96 | Cliff: 95%, WAR: +0.32 | MIT |
| Qdrant Qdrant ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 96, Fit: 95, Wave: 95.48 | Cliff: 95%, WAR: +0.29 | Apache-2.0 |
| LanceDB (Columnar Lance Format) LanceDB ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 96, Fit: 95, Wave: 95.16 | Cliff: 95%, WAR: +0.3 | Apache-2.0 |
| sqlite-vec Alex Garcia ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 98, Fit: 96, Wave: 93.9 | Cliff: 96%, WAR: +0.27 | MIT |
| Weaviate Weaviate ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 93, Fit: 93, Wave: 93.44 | Cliff: 93%, WAR: +0.24 | BSD-3-Clause |
| Milvus Zilliz / LF AI ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 91, Fit: 93, Wave: 92.92 | Cliff: 91%, WAR: +0.23 | Apache-2.0 |
| Elasticsearch Vector & BM25 Elastic ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 94, Fit: 94, Wave: 92.04 | Cliff: 93%, WAR: +0.26 | AGPL-3.0 |
| Redis / RediSearch Vector Redis ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 96, Fit: 94, Wave: 91.56 | Cliff: 93%, WAR: +0.25 | AGPL-3.0 |
| Neo4j Graph + Vector Neo4j ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 92, Fit: 93, Wave: 90.56 | Cliff: 91%, WAR: +0.24 | GPL-3.0 |
| MongoDB Atlas Vector Search MongoDB ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 93, Fit: 93, Wave: 90.52 | Cliff: 93%, WAR: +0.21 | SSPL-1.0 |
| Chroma Chroma ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 90, Fit: 92, Wave: 90.08 | Cliff: 89%, WAR: +0.2 | Apache-2.0 |
| Cloudflare D1 (Version-Fenced SQLite) Cloudflare ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 97, Fit: 95, Wave: 89.12 | Cliff: 95%, WAR: +0.3 | Proprietary |
| Pinecone Serverless Pinecone ( storage_vector_backend) |
vector_and_transactional_storage |
EMPIRICAL_LEADER | Exec: 95, Fit: 94, Wave: 87.96 | Cliff: 93%, WAR: +0.23 | Proprietary |