most citedOpen Biomedical Knowledge Graphs at Scale: Construction, Federation, and AI Agent Access with Samyama Graph Database

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cs.DB2026

Same Pattern, Different Answer: A Reference Semantics and Divergence Map for GQL and SQL/PGQ Path Patterns

Madhulatha Mandarapu, Sandeep Kunkunuru

GQL (ISO/IEC 39075:2024) is the first international standard for a graph query language, and SQL/PGQ (ISO/IEC 9075-16:2023) embeds the same pattern-matching core, GPML, in SQL. Bot…

cs.DB2026

Bounded, Indeterminate, or a Bug: A Condition-Aware Oracle for Differential Testing of SQL Aggregates

Madhulatha Mandarapu, Sandeep Kunkunuru

Differential database testing compares results across engines and calls a discrepancy a bug. For floating-point aggregates this is unsound: engines legitimately disagree because fl…

cs.DB2026

The Decode-Work Law: Margin-Governed, Provably-Exact Spatial Joins over Compressed Geometry

Madhulatha Mandarapu, Sandeep Kunkunuru

Filter-and-refine spatial joins have always avoided touching exact geometry for certified candidate pairs, but the field never modeled the decompression cost of the pairs that surv…

cs.DB2026

When to Repair a Graph ANN Index: A Matched-Budget Negative Result, and the Interpolated-Baseline Trap That Hid It

Madhulatha Mandarapu, Sandeep Kunkunuru

Graph approximate-nearest-neighbor (ANN) indexes (HNSW, DiskANN/Vamana) lose recall under insert/delete churn, because deletions orphan the greedy-search paths that route through r…

cs.DB2026

Knowledge Graphs as the Missing Data Layer for LLM-Based Industrial Asset Operations

Madhulatha Mandarapu, Sandeep Kunkunuru

LLM-based agents for industrial asset operations show limited accuracy when reasoning over flat document stores. AssetOpsBench (KDD 2026) establishes that GPT-4 agents achieve 65%…

cs.DB2026

One Index for Subsumption and Roll-up across Time, Geography, and Ontology

Madhulatha Mandarapu, Sandeep Kunkunuru

Time-series, geospatial, and ontology systems each maintain a hierarchy -- day <= month <= year, zip <= city, is-a / part-of -- and each indexes it in a separate silo. We observe t…

cs.DB2026

When Is a Columnar Scan Bandwidth-Bound? A Decode-Throughput Law and Its Cross-Hardware Validation

Madhulatha Mandarapu, Sandeep Kunkunuru

A columnar scan that decompresses, filters, and aggregates should be limited only by memory bandwidth (the roofline floor T >= BytesRead/beta), yet real kernels are often compute-b…

cs.DB2026

Caching for Dollars, Not Hits: An Exact Offline Reference for Cloud-Egress Caching and the Crossover That Decides When It Pays

Madhulatha Mandarapu, Sandeep Kunkunuru

When a cache miss fetches from cloud object storage, the bill is per GET request and per byte of egress, not latency. Classic caching minimizes the miss rate, the wrong objective:…

cs.DB2026

Group Commit Self-Clocks: Why Tuning Is Unnecessary Above a Device-Set Load Threshold

Madhulatha Mandarapu, Sandeep Kunkunuru

Group commit amortizes the fixed cost of a durable log flush across many committing transactions; the release rule - a timer, a batch size, or an adaptive policy - is a classic tun…

cs.DB2026

The Value of Adaptivity in LSM Bloom-Filter Tuning: A Log-Law and a Two-Clock Frontier

Madhulatha Mandarapu, Sandeep Kunkunuru

Log-structured merge (LSM) trees attach an approximate-membership filter to every run and must split a fixed memory budget across them. The static optimum is known (Monkey); a larg…

cs.DB2026

When Does q-error Predict Plan Regret? Three Regimes of Cardinality-Estimation Error

Madhulatha Mandarapu, Sandeep Kunkunuru

Cardinality-estimation (CE) research ranks estimators by q-error, yet it is well known that q-error is an imperfect proxy for query-plan quality. We give a measurement-driven accou…

cs.DB2026

Graph-Grounded Optimization: Rao-Family Metaheuristics, Classical OR, and SLM-Driven Formulation over Knowledge Graphs

Madhulatha Mandarapu, Sandeep Kunkunuru

We propose graph-grounded optimization: a paradigm in which the decision variables, constraints, and objective coefficients of a real-world optimization problem are sourced from a…

cs.DB2026★ 1 cited

Open Biomedical Knowledge Graphs at Scale: Construction, Federation, and AI Agent Access with Samyama Graph Database

Madhulatha Mandarapu, Sandeep Kunkunuru

Biomedical knowledge is fragmented across siloed databases -- Reactome for pathways, STRING for protein interactions, ClinicalTrials.gov for study registries, DrugBank for drug voc…

cs.DB2026

Samyama: A Unified Graph-Vector Database with In-Database Optimization, Agentic Enrichment, and Hardware Acceleration

Madhulatha Mandarapu, Sandeep Kunkunuru

Modern data architectures fragment across graph databases, vector stores, analytics engines and optimization solvers, forcing ETL between them. We present Samyama, a graph-vector d…