Articles by MinervaDB Corporation

About MinervaDB Corporation

Full-stack Database Infrastructure Architecture, Engineering and Operations Consultative Support(24*7) Provider for PostgreSQL, MySQL, MariaDB, MongoDB, ClickHouse, Trino, SQL Server, Cassandra, CockroachDB, Yugabyte, Couchbase, Redis, Valkey, NoSQL, NewSQL, SAP HANA, Databricks, Amazon Resdhift, Amazon Aurora, CloudSQL, Snowflake and AzureSQL with core expertize in Performance, Scalability, High Availability, Database Reliability Engineering, Database Upgrades/Migration, and Data Security.

Enterprise RAG architecture inside a customer VPC: sources, ingestion with ACLs, pgvector or Milvus chunk store, hybrid retrieval, constrained generation, golden set and audit log

Enterprise RAG Architecture in Your Own VPC: 5 Proven Layers on pgvector or Milvus

The demos all work. A few hundred documents, a hosted embedding API, a vector index, a chat window, and the answers look right. What we get asked to fix is what happens after that: the [...]

Model drift monitoring on ClickHouse: prediction log, label log, reference bins, daily aggregate states, signals, thresholds and routing

Model Drift Monitoring on ClickHouse: 4 Proven Signals, Thresholds Tied to Money

A model does not fail loudly. It keeps returning scores in the right range, the service stays green, and the business notices six weeks later that approval rates moved or fraud losses climbed. By then [...]

Master data management on PostgreSQL: source, candidate, master, attribute lineage, effective-dated crosswalk and history tables

Master Data Management on PostgreSQL: 6 Proven Tables That Make Every Golden Record Explainable

Most master data management programmes we are asked to rescue did not fail on matching algorithms. They failed because nobody could answer, for a given customer number on a given invoice, which source system's address [...]

Metrics layer on dbt and MetricFlow: sources, marts, semantic models and metrics compiled into BI, notebook and decision API queries

Metrics Layer with dbt: 5 Proven Tests That Keep One Definition per Number

Ask three teams in the same company for last quarter's net revenue and you will usually get three numbers. Finance excludes returns booked after period close, marketing counts gross of discounts because that is what [...]

Feature store architecture on PostgreSQL, ClickHouse and Valkey: registry, two write paths, offline store, online store, prediction log and SLOs

Feature Store Architecture: 7 Proven Decisions on PostgreSQL and ClickHouse

A feature store architecture is three contracts, not a product. The first contract is that a feature has exactly one definition, one owner and one freshness promise. The second is that any training set can [...]

Retail Data Strategy: 6 Proven Layers for Marketing and Sales Ops Analytics

A retail data strategy is not a tooling decision. It is a set of commitments about four facts that marketing and sales operations both depend on and rarely agree about: who the customer is, what [...]

Azure SQL Performance Troubleshooting: 7 Proven Steps

Azure SQL performance troubleshooting starts in a different place from on-premises SQL Server work. There is no operating system to inspect, no sys.dm_os_wait_stats that means what it used to, and the first suspect is almost [...]

Data Analytics

Databricks Long-Running Queries: 6-Step Troubleshooting Guide

Databricks long-running queries are rarely one problem. When a statement that used to finish in forty seconds starts taking nine minutes, the nine minutes are usually spread across a cold warehouse, a queue, a compilation [...]

Expensive SQL on Exadata 26.1: Read the Offload Numbers Before You Build the Index

The Exadata ticket we see most often is not about a slow query. It is about a cluster that runs hot for hours, an IORM plan that somebody keeps re-tuning, and a licence conversation about [...]

SQL Server 2025 Expensive Queries: 7 Proven Ways to Find and Fix Them by Latency and Resource Cost

"Expensive queries" is a phrase that hides two different problems. One is response time: a statement the application waits too long for. The other is resource efficiency: a statement that burns CPU, logical reads and [...]