MinervaDB University: Advanced Database Training for Data & AI Leaders

MinervaDB University is the executive education and deep-technology arm of MinervaDB Inc. — an invitation-grade destination for advanced database training built exclusively for Principal Data Architects, Data Scientists, Chief Data Officers, CTOs, and technology leadership executives with a deep commitment to AI, Data, and ML. There are no beginner tracks here. No introductory slideware. Every program at MinervaDB University is an Advanced Program: three to five days of intense, hands-on engineering, eight hours a day, delivered live over Zoom by Shiv Iyer — Founder & CEO of MinervaDB and ChistaDATA, former Principal Database Architect at MySQL and Sun Microsystems — and a hand-picked faculty of Senior Principal engineers who run mission-critical data infrastructure for 900+ enterprises worldwide.

This is advanced database training the way it should be taught: at the level of optimizer internals, storage engines, replication protocols, and production war rooms — across PostgreSQL, MySQL, MariaDB, Microsoft SQL Server, MongoDB, SAP HANA, ClickHouse, Trino, Apache Cassandra, Redis, Valkey, Milvus, and every major cloud DBaaS on AWS, Azure, and GCP.

The Two Advanced Programs at a Glance

Advanced Database Training Program	Duration	Delivery	Fee (US $)	Core Coverage
Program 1 — Enterprise OLTP & Cloud Database Architecture Masterclass	5 days × 8 hours	Live online (Zoom), hands-on	$4,550.00 · early enrollment $3,835.00	PostgreSQL, MySQL, MariaDB, Microsoft SQL Server, MongoDB, SAP HANA, and all major cloud DBaaS
Program 2 — Real-Time Analytics, AI & Vector Data Infrastructure Masterclass	4 days × 8 hours	Live online (Zoom), hands-on	$3,640.00 · early enrollment $2,600.00	ClickHouse, Trino, Apache Cassandra, Redis, Valkey, Milvus, Kafka pipelines, and analytics/AI cloud platforms

Two advanced database training programs, one curriculum architecture — every engine and cloud platform that matters to data leadership.

Table of Contents

• The Two Advanced Programs at a Glance
• Why MinervaDB University Exists
• What Makes This Advanced Database Training Different
• Who Should Attend
• Program 1 — Enterprise OLTP & Cloud Database Architecture Masterclass (5 Days)
• Program 2 — Real-Time Analytics, AI & Vector Data Infrastructure Masterclass (4 Days)
• How the Workshops Are Delivered
• Faculty: Shiv Iyer and the Senior Principals
• The MinervaDB Research Library
• Fees, Cohorts & Enrollment
• What You Walk Away With
• Certification & Alumni Network
• Frequently Asked Questions
• Reserve Your Seat

Why MinervaDB University Exists

Most database training on the market — and nearly every advanced database training course sold today — is written for administrators learning a single product. It teaches you where the buttons are. It does not teach you how a B-tree page split interacts with fill factor under a hot sequential key, why a distributed query planner chooses a broadcast join over a partitioned one, or how to design an error budget for a petabyte-scale analytics platform that feeds a production ML pipeline.

The people who carry those decisions — Principal Data Architects, CDOs, CTOs, senior Data Scientists — have nowhere serious to go. Vendor certification tracks are too shallow. Conference talks are too short. Internal enablement is too narrow. MinervaDB University was founded to close that gap with advanced database training delivered at genuine principal-engineer depth, by people who have spent twenty-plus years inside the engines themselves.

MinervaDB Inc. operates one of the world's most respected vendor-neutral database practices: full-stack data engineering, 24×7 consultative support, and remote DBA services for more than 900 enterprises — from Wall Street trading platforms to global AdTech, SaaS, fintech, and healthcare estates. MinervaDB University distills that operating experience into two elite advanced database training programs. Everything taught in these workshops has been proven in production, under load, at scale, with revenue on the line.

What Makes This Advanced Database Training Different

Five principles govern every MinervaDB University advanced database training program. They are non-negotiable, and they are the reason seats are limited and demand outstrips capacity.

1. Advanced Programs only — no foundations, ever

Every cohort assumes you already operate databases in production. This advanced database training starts where vendor curricula end: optimizer cost models, MVCC and vacuum internals, InnoDB redo/undo mechanics, MergeTree part lifecycle, WiredTiger checkpointing, HANA delta merge, Cassandra compaction strategies, Raft and quorum mathematics, cache eviction theory, and vector index construction (HNSW, IVF, DiskANN). If a topic can be learned from a getting-started guide, it is not on our whiteboard.

2. Hands-on, not hand-waving

Each participant receives dedicated cloud lab environments — real clusters, real datasets, real failure injection. You will read query plans with EXPLAIN (ANALYZE, BUFFERS), walk system.query_log and system.parts telemetry, break replication on purpose, and repair it under a running clock. Roughly 60% of every advanced database training day is lab time.

3. Taught by practitioners who wrote the playbooks

Every advanced database training program is led personally by Shiv Iyer, with Senior Principal engineers from MinervaDB's global consulting bench — the same people who architect, rescue, and operate production estates for our enterprise clients. Faculty never exceeds a 1:5 instructor-to-participant ratio during labs.

4. Vendor-neutral by principle

MinervaDB sells no licenses and carries no vendor quota. When PostgreSQL is the wrong answer, we say so. When a managed DBaaS will cost you 4× at scale, we show you the arithmetic. This intellectual honesty is the foundation of our advanced database training — and the reason CDOs and CTOs trust our recommendations enough to take them to their boards.

5. Measurement over opinion

Every recommendation in this advanced database training is anchored to a named metric, catalog view, or system table — pg_stat_statements, performance_schema, Query Store, system.trace_log, M_ monitoring views, nodetool histograms. You leave knowing not just what to do, but how to prove it was the right call.

Who Should Attend

This advanced database training is engineered for a specific, senior audience. Cohorts are curated deliberately so that peer discussion happens at the right altitude.

• Principal & Distinguished Data Architects — accountable for multi-engine, multi-cloud data platform design and the trade-offs that decide a company's next five years.
• Senior Data Scientists & ML Platform Engineers — who need production-grade command of the data infrastructure beneath their models: feature stores, vector search, real-time pipelines, and RAG architectures.
• Chief Data Officers — who must govern AI-era data estates, evaluate build-vs-buy honestly, and interrogate vendor claims with technical confidence.
• CTOs and VPs of Engineering — who own database spend, reliability targets, and the engineering culture around data.
• Technology leadership executives with a deep, board-level commitment to AI, Data, and ML transformation.

Participants are expected to arrive with production experience. Enrollment includes a short technical intake so faculty can calibrate labs to your estate — engines in production, data volumes, cloud footprint, and the decisions you are currently facing.

Program 1 — Enterprise OLTP & Cloud Database Architecture Masterclass

Duration: 5 days × 8 hours (40 hours) · Delivery: Live online via Zoom · Format: Hands-on Advanced Program · Fee: US $4,550.00 (early-enrollment US $3,835.00)

The definitive advanced database training for enterprise transactional and mixed-workload estates. Program 1 spans PostgreSQL (18 and 17), MySQL (8.4 LTS and the 9.x innovation track), MariaDB (11.8 LTS), Microsoft SQL Server (2022/2025), MongoDB (8.0), and SAP HANA — plus the managed incarnations of each on every major cloud: Amazon RDS, Aurora, Azure SQL Database, Azure Database for PostgreSQL/MySQL, Google Cloud SQL, AlloyDB, and MongoDB Atlas.

Day 1 — Storage Engine & Optimizer Internals Across Engines

Advanced database training begins where the data lives: on disk and in memory.

The day the rest of the week is built on. PostgreSQL heap architecture, MVCC, visibility maps, TOAST, and the planner's cost model; InnoDB redo/undo, change buffering, adaptive hash index, and MySQL's cost-based optimizer; MariaDB optimizer divergence and MyRocks; SQL Server's cardinality estimator, Query Store, and intelligent query processing; MongoDB WiredTiger internals; SAP HANA column store, delta merge, and plan cache. Labs: dissecting execution plans on identical schemas across all six engines and explaining — precisely — why each optimizer chose differently.

Day 2 — Performance Engineering & Query Optimization at Scale

Systematic, measurement-first tuning methodology. Wait-event analysis, pg_stat_statements and auto_explain, performance_schema and sys schema, SQL Server Query Store forensics, HANA M_EXPENSIVE_STATEMENTS, MongoDB profiler. Index engineering in depth: covering indexes, partial and expression indexes, index-only scans, clustered vs heap trade-offs, columnstore for HTAP. Connection architecture with PgBouncer and ProxySQL. Labs: each participant tunes a deliberately degraded 500-GB workload and must defend every change with before/after telemetry.

Day 3 — High Availability, Replication & Disaster Recovery Engineering

Streaming and logical replication in PostgreSQL with Patroni-orchestrated failover; MySQL Group Replication and Galera semantics (certification, flow control, split-brain); SQL Server Always On Availability Groups and quorum design; MongoDB replica set elections and write concerns; HANA System Replication modes and takeover mechanics. RPO/RTO engineering as a financial calculation. Backup theory that survives auditors: PITR, pgBackRest, XtraBackup, snapshot strategies, and restore drills. Labs: forced failovers with data-loss forensics — participants measure their actual RPO, not their assumed one.

Day 4 — Cloud DBaaS Architecture, Economics & Exit Strategy

The deepest treatment of managed database services in any advanced database training program. Aurora's decoupled storage architecture vs vanilla RDS; AlloyDB's columnar engine; Azure SQL Hyperscale; Atlas topology and search nodes; DynamoDB, Cosmos DB, Spanner, and Bigtable for planet-scale patterns; ElastiCache and Memorystore; Redshift and BigQuery boundary-setting. Managed-vs-self-managed divergence maps: what each provider silently changes, restricts, or lags. Cloud database FinOps: reserved capacity arithmetic, I/O pricing traps, egress-aware DR design, and negotiating leverage. Labs: participants build a defensible TCO model and an exit plan for a reference estate.

Day 5 — Architecture Council: Capstone Design Review

The advanced database training capstone that alumni talk about for years.

The signature MinervaDB University experience. Participants bring an anonymized architecture from their own estate — or select one of our production-derived case studies — and present it to the Architecture Council: Shiv Iyer and the Senior Principal faculty, in the same review format we run for Fortune 500 consulting clients. Sharding strategy, wraparound risk, HA topology, security posture, compliance boundaries, and cost structure are challenged line by line. Every participant leaves with a written, prioritized architecture assessment of their design.

Program 2 — Real-Time Analytics, AI & Vector Data Infrastructure Masterclass

Duration: 4 days × 8 hours (32 hours) · Delivery: Live online via Zoom · Format: Hands-on Advanced Program · Fee: US $3,640.00 (early-enrollment US $2,600.00)

The advanced database training program for the AI-era data platform: columnar analytics, federated SQL, wide-column scale, in-memory data structures, and vector search — the infrastructure beneath modern ML and GenAI systems. Program 2 spans ClickHouse (25.x LTS), Trino, Apache Cassandra (5.0), Redis (8.x), Valkey (9.x), and Milvus (2.6) — plus ClickHouse Cloud, Confluent, DataStax Astra, Redis Cloud, ElastiCache, MemoryDB, Snowflake, and Databricks as comparative managed platforms. Real-time analytics content is delivered with the full depth of our sister practice ChistaDATA Inc., the world's dedicated ClickHouse infrastructure operations company.

Day 1 — ClickHouse Internals & Columnar Performance Engineering

MergeTree family internals at production depth: sort-key design, partitioning strategy, index granularity, skip indexes, projections, and materialized-view topology; the part lifecycle, merges, and mutations; ReplicatedMergeTree and ClickHouse Keeper quorum design; S3-backed tiered storage. Performance engineering through system.query_log, system.parts, system.merges, system.trace_log, and EXPLAIN PIPELINE — engineering for p95/p99 latency and sustained ingestion throughput. ClickHouse Cloud vs open-source divergence (SharedMergeTree) examined honestly. Labs: participants take a 2-billion-row dataset from 9-second scans to sub-100-millisecond analytical queries and document every step of the telemetry trail.

Day 2 — Federated SQL, Wide-Column Scale & Streaming Ingestion

Trino as the federation layer: cost-based optimization across catalogs, dynamic filtering, fault-tolerant execution, and lakehouse patterns over Iceberg and Delta. Apache Cassandra 5.0 at depth: partition-key mathematics, storage-attached indexes, compaction strategy selection, tombstone pathology, and multi-DC replication. Streaming ingestion architecture: Kafka topology, Debezium CDC into analytical stores, exactly-once semantics, and backpressure engineering. Labs: build a federated query layer across ClickHouse, Cassandra, and object storage; design and defend a partition key under a simulated 1M-writes/second workload.

Day 3 — In-Memory Data Systems: Redis & Valkey Engineering

The post-fork landscape treated with vendor-neutral rigor: Redis 8.x licensing and in-core JSON/search/vector capabilities vs Valkey's BSD-licensed engine and module ecosystem — and what the diverging threading models (Redis io-threads vs Valkey async I/O) mean for tail latency. Memory engineering: encodings, eviction policies, fragmentation forensics. Persistence trade-offs (RDB/AOF), replication, Sentinel, and Cluster architecture; caching topologies, hot-key mitigation, and client-side caching. Cloud mapping across ElastiCache, MemoryDB, Memorystore, and Azure Managed Redis. Labs: latency engineering under load with full instrumentation, plus a Redis-to-Valkey migration executed live.

Day 4 — Vector Databases, RAG Infrastructure & the AI Data Platform Capstone

Milvus internals: HNSW, IVF, and DiskANN index construction and recall/latency/cost trade-offs; segment lifecycle, GPU acceleration, and scaling topology. The honest comparison every AI leader needs: dedicated vector databases vs pgvector, vs vector capabilities in Redis, Valkey, Cassandra, and ClickHouse — with decision criteria anchored in measured recall and cost curves, not vendor benchmarks. Production RAG architecture: embedding pipelines, hybrid search, reranking, evaluation, and private in-VPC GenAI deployment with GDPR/DPDP/HIPAA-class governance. Capstone: participants design an end-to-end real-time AI data platform — ingestion through vector serving — and defend it before the Architecture Council.

The end-to-end AI data platform participants design, build, and defend — from ingestion to governed GenAI.

Complete Engine & Cloud DBaaS Coverage

No other advanced database training program covers this breadth at this depth. Across the two advanced database training programs, MinervaDB University delivers principal-level instruction on thirteen engines and every major managed database service in the market.

Transactional & enterprise engines (Program 1)

• PostgreSQL 17/18 — planner internals, MVCC and autovacuum engineering, logical and streaming replication, Patroni HA, PgBouncer pooling, Citus sharding, pgvector, TimescaleDB, wraparound prevention, and PostGIS at scale.
• MySQL 8.4 LTS / 9.x — InnoDB internals, Group Replication and Galera, ProxySQL traffic engineering, online schema change at scale, and HeatWave evaluated with vendor-neutral honesty.
• MariaDB 11.8 LTS — optimizer divergence from MySQL, system-versioned tables, MaxScale failover engineering, MyRocks and ColumnStore storage engines, and bidirectional MySQL↔MariaDB migration strategy.
• Microsoft SQL Server 2022/2025 — Always On Availability Groups, Query Store forensics, intelligent query processing, columnstore HTAP patterns, and Azure SQL migration engineering.
• MongoDB 8.0 — WiredTiger internals, shard-key design and resharding, replica-set election mechanics, and Atlas topology and cost governance.
• SAP HANA — column store and delta merge internals, memory management and NSE warm data, HANA System Replication, and workload management for S/4HANA-era estates.

Analytics, in-memory & AI engines (Program 2)

• ClickHouse 25.x LTS — the full MergeTree discipline: sort keys, partitioning, skip indexes, projections, materialized views, Keeper quorum design, tiered storage, and p99 latency engineering.
• Trino — federated cost-based optimization, dynamic filtering, fault-tolerant execution, and lakehouse query patterns over Iceberg and Delta.
• Apache Cassandra 5.0 — partition mathematics, storage-attached indexes, compaction strategy engineering, and multi-DC replication design.
• Redis 8.x & Valkey 9.x — memory encodings, persistence trade-offs, Cluster architecture, the post-fork licensing landscape, and live migration engineering between the two.
• Milvus 2.6 — HNSW/IVF/DiskANN index internals, recall-latency-cost tuning, and production vector serving topology for RAG and semantic search.

Every major cloud DBaaS

Both advanced database training programs treat managed services as first-class subjects, not afterthoughts: Amazon RDS, Aurora, DynamoDB, ElastiCache, MemoryDB, Keyspaces, and Redshift on AWS; Azure SQL Database, Azure Database for PostgreSQL and MySQL, Cosmos DB, and Azure Cache on Microsoft Azure; Cloud SQL, AlloyDB, Spanner, Bigtable, Memorystore, and BigQuery on Google Cloud; plus MongoDB Atlas, ClickHouse Cloud, Confluent, DataStax Astra, Redis Cloud, Snowflake, and Databricks. For each, faculty maintain explicit divergence maps — what the managed service changes, restricts, or lags relative to the open-source engine — because architecture decisions made without that map are guesses.

Advanced Database Training for the AI Era

Every enterprise is now an AI company — and every AI initiative lives or dies on its data infrastructure. Feature freshness, vector recall, ingestion latency, and governance boundaries are database problems before they are ML problems. Yet most data science leaders have never been taught how the engines beneath their models actually behave under production load.

MinervaDB University was built for this moment. Program 2 is, to our knowledge, the only advanced database training program that connects columnar analytics internals, streaming ingestion, in-memory data structures, and vector index construction into a single coherent AI data platform doctrine — taught hands-on, with governance patterns for GDPR, DPDP, and HIPAA-class environments built in rather than bolted on. Program 1 supplies the enterprise backbone those AI workloads depend on: transactional integrity, high availability, and cloud economics under control.

For CDOs and CTOs, the two programs together form a complete executive curriculum for the AI-data decade: what to build, what to buy, what to measure, and how to know when a vendor is telling you a story. Leadership teams pursuing this agenda at organizational scale should also review our GCC Data Leadership practice and database transformation programs for CIOs.

MinervaDB University vs. Typical Vendor Training

Executives evaluating advanced database training deserve a direct comparison. Typical vendor training is product-scoped, junior-calibrated, slide-driven, and taught by professional trainers who have never carried a production pager. It optimizes for certificate throughput. MinervaDB University advanced database training programs are estate-scoped rather than product-scoped: thirteen engines and every major cloud, because that is what real enterprises run. They are senior-calibrated: cohorts of principal architects and executives, never mixed with beginners. They are lab-driven: roughly 60% hands-on, on dedicated per-participant clusters. And they are taught by the practitioners other consultancies benchmark against — with every claim anchored in telemetry you can reproduce on your own systems the following week.

The result is a different category of outcome. Certification training changes what is on your résumé. MinervaDB University changes what happens in your production environment, your cloud bill, and your AI roadmap.

How Enrollment Works

Enrollment in MinervaDB University advanced database training is deliberately simple and deliberately selective — four steps from enquiry to cohort:

• 1. Request the cohort calendar. Book an appointment or write to the MinervaDB University desk with your preferred program and quarter.
• 2. Complete the technical intake. A short structured questionnaire covering your production engines, data volumes, cloud footprint, and the architecture decisions ahead of you. Faculty read every intake personally.
• 3. Receive your seat confirmation. Seats are allocated on intake acceptance to protect cohort seniority and peer quality. Early-enrollment pricing applies 45 or more days before cohort start.
• 4. Pre-program provisioning. Ten days before the cohort begins, you receive lab credentials, the pre-reading dossier from the MinervaDB Research Library, and the Zoom calendar for your cohort window.

The executive learning journey: day-by-day intensity, capped cohorts, and consulting-grade deliverables.

How the Workshops Are Delivered

Both advanced database training programs are delivered 100% online, live over Zoom — engineered deliberately so that senior leaders in any timezone can attend without surrendering a week of travel. But "online" at MinervaDB University does not mean webinar. It means a working session with cameras on, terminals open, and faculty watching your telemetry alongside you.

The daily rhythm of the advanced database training day

Each workshop day runs eight hours, structured for sustained intensity: a 90-minute internals deep-dive to open the day, followed by alternating lab blocks and design discussions, and closing with a moderated architecture debrief where the day's findings are pressure-tested against real production scenarios drawn from MinervaDB's consulting archive. Advanced database training sessions are scheduled with Americas-friendly and EMEA/APAC-friendly cohort windows; every session is recorded, and recordings remain available to participants for twelve months.

Dedicated lab infrastructure

Every participant receives an individual, pre-provisioned cloud lab estate for the duration of the program — multi-node clusters for each engine on the syllabus, seeded with realistic datasets at meaningful scale, plus failure-injection tooling. Nothing is simulated on slides. When we discuss Patroni failover, you fail over your own cluster. When we discuss ClickHouse merges, you watch your own system.merges. Labs stay live for seven days after the program ends so you can rerun every exercise.

Small cohorts, deliberately

Enrollment is capped at fifteen participants per cohort. This is an economic sacrifice and a pedagogical necessity: at this depth, advanced database training only works when faculty can look at your screen, challenge your reasoning, and adapt the material to the estates represented in the room. Cohorts regularly include architects and executives from Fortune 500 enterprises, high-growth AI companies, global banks, and national-scale platforms — the peer network alone justifies the seat for many alumni.

Faculty: Shiv Iyer and the Senior Principals

MinervaDB University advanced database training programs are personally designed and led by Shiv Iyer, Founder & CEO of MinervaDB Inc. and ChistaDATA Inc. Shiv's career spans more than two decades at the center of the open-source database world: Principal Database Architect at MySQL and Sun Microsystems, senior leadership at Percona and PalominoDB, and architect-of-record for some of the largest PostgreSQL, MySQL, and ClickHouse estates in production today. He is a prolific author on database internals — optimizer mechanics, storage engines, performance engineering — and a frequent speaker at conferences worldwide. Very few people alive have tuned as many production database systems, across as many engines, as your lead instructor.

Shiv teaches alongside a rotating faculty of Senior Principal engineers drawn from MinervaDB's and ChistaDATA's global consulting bench — specialists in PostgreSQL internals, SQL Server Always On, MongoDB distributed systems, SAP HANA, Cassandra at petabyte scale, Redis/Valkey engineering, and production vector search. These are not professional trainers reading courseware; they are the engineers our enterprise clients call at 2 a.m. Faculty for each cohort is selected to match the estates and priorities declared in participant intakes.

The MinervaDB Research Library: Included With Every Seat

Every participant receives twelve months of access to the exhaustive research works of MinervaDB — the internal knowledge system that powers our consulting practice, and one of the most valuable components of this advanced database training. No other program includes anything comparable. The library spans:

• Architecture blueprints and reference designs — field-proven topologies for HA, DR, sharding, multi-region, and hybrid-cloud deployments across every engine we teach.
• Performance engineering research — deep-dive studies on optimizer behavior, storage-engine mechanics, benchmark methodology, and tuning playbooks, continuously updated as engine versions evolve.
• Migration engineering dossiers — assessment frameworks and cutover runbooks for moves between engines and off proprietary platforms, including warehouse migrations into ClickHouse.
• Runbook and SOP templates — the same versioned, review-gated operational document standards MinervaDB ships to enterprise support clients, ready to adapt to your organization.
• Cloud DBaaS economics research — managed-service divergence maps and cost-model worksheets across AWS, Azure, GCP, and vendor clouds.
• AI data infrastructure research — vector search evaluations, RAG architecture patterns, and private GenAI deployment frameworks with governance guidance for GDPR, DPDP, and HIPAA-class environments.

Alumni consistently describe the research library as the gift that keeps compounding: the advanced database training teaches you how to think; the library ensures your teams execute to the same standard long after the program ends. Our public engineering blog offers a small taste of the depth inside.

Fees, Cohorts & Enrollment

Program fees range from US $2,600.00 to US $4,550.00 per participant, depending on the program and enrollment window. Advanced database training fees at MinervaDB University are all-inclusive: instruction, dedicated lab infrastructure, twelve months of session recordings, the complete MinervaDB Research Library subscription, and the capstone Architecture Council review.

• Program 1 — Enterprise OLTP & Cloud Database Architecture Masterclass: 5 days · 40 hours · US $4,550.00 standard · US $3,835.00 early enrollment (45+ days before cohort start).
• Program 2 — Real-Time Analytics, AI & Vector Data Infrastructure Masterclass: 4 days · 32 hours · US $3,640.00 standard · US $2,600.00 early enrollment (45+ days before cohort start, limited seats).
• Dual-program enrollment: executives attending both programs within twelve months receive priority seating and preferential pricing on the second program — enquire when booking.
• Private cohorts: both Advanced Programs can be delivered as private, customized cohorts for a single leadership team, with curriculum calibrated to your estate. Contact MinervaDB for private cohort scheduling.

Advanced database training seats are limited to fifteen per cohort and are allocated on acceptance of the technical intake, not on payment order. Cohorts for the current quarter routinely close early — leaders who know the value of this caliber of faculty do not wait.

What You Walk Away From This Advanced Database Training With

MinervaDB University measures the success of its advanced database training the way our consulting practice does: by what changes in production after the engagement. Graduates of this advanced database training leave with capabilities that compound for years.

• Engine-internals fluency across PostgreSQL, MySQL, MariaDB, SQL Server, MongoDB, SAP HANA, ClickHouse, Trino, Cassandra, Redis, Valkey, and Milvus — the ability to reason from storage format to query plan to SLA on any of them.
• A measurement-first operating doctrine — every performance and architecture decision anchored to named telemetry, defensible in front of any board or auditor.
• A written architecture assessment of your own design from the capstone Architecture Council review — a deliverable many participants take directly into their planning cycles.
• Cloud DBaaS command — the divergence maps, cost models, and exit strategies to negotiate with hyperscalers from a position of technical strength.
• An AI data platform blueprint — production-grade patterns for real-time analytics, vector search, and governed GenAI infrastructure.
• Twelve months of the MinervaDB Research Library and membership in an elite alumni network of principal architects and data executives worldwide.
• A MinervaDB University Certificate of Advanced Completion for each program, signed by the faculty.

Frequently Asked Questions

Is this advanced database training suitable for someone new to databases?

No — by design. MinervaDB University offers advanced database training programs only. Participants are expected to operate production database systems today and to arrive comfortable with SQL, replication concepts, and cloud infrastructure. The technical intake protects cohort quality for everyone.

Is the advanced database training live and hands-on, or recorded lectures?

Every session is live on Zoom, taught in real time by Shiv Iyer and the Senior Principal faculty, with roughly 60% of each day spent in your own dedicated lab environment. Recordings are provided afterward for reference, but this is a working workshop, not a video course.

Which advanced database training program should I attend first?

If your estate is primarily transactional — PostgreSQL, MySQL, MariaDB, SQL Server, MongoDB, SAP HANA, and their cloud DBaaS incarnations — begin with Program 1. If your mandate is analytics, streaming, or AI/ML infrastructure — ClickHouse, Trino, Cassandra, Redis, Valkey, Milvus — begin with Program 2. Many CDOs and CTOs attend both within a year; the programs are complementary by design.

Do you cover our specific versions and cloud providers?

Yes. Every advanced database training curriculum is version-pinned to current production reality (PostgreSQL 17/18, MySQL 8.4 LTS, MariaDB 11.8 LTS, SQL Server 2022/2025, MongoDB 8.0, ClickHouse 25.x LTS, Cassandra 5.0, Redis 8.x, Valkey 9.x, Milvus 2.6) and every major cloud DBaaS on AWS, Azure, and GCP is treated as a first-class subject, with managed-vs-self-managed divergence examined explicitly. Intake responses shape which services receive extra lab time in your cohort.

What does the fee include — and what does it not?

The fee (US $2,600.00–$4,550.00 depending on program and enrollment window) includes all instruction, dedicated per-participant lab infrastructure, twelve months of recordings, the full MinervaDB Research Library subscription, the Architecture Council capstone review, and certification. It does not include consulting engagements on your production systems — though many organizations follow the program with a formal MinervaDB engagement, and alumni receive priority scheduling.

Can we run private advanced database training for our leadership team?

Yes. Both advanced database training programs are available as private cohorts with curriculum calibrated to your estate under NDA. Private cohorts are the preferred route for organizations sending five or more senior leaders. Book an appointment to scope one.

Reserve Your Seat at MinervaDB University

The database decisions made by your principal architects and data executives this year will echo through your infrastructure, your cloud bill, and your AI roadmap for a decade. MinervaDB University exists so those decisions are made by leaders trained at the deepest level the industry offers — in advanced database training programs taught by the engineers other experts call.

Two advanced database training programs. Five days or four. Eight hours a day, live on Zoom, hands-on from the first hour. Faculty led by Shiv Iyer. Cohorts capped at fifteen. Research library included. US $2,600.00–$4,550.00.

Book an appointment with MinervaDB to request the current cohort calendar, complete your technical intake, and reserve your seat — or explore our consulting practice and Data Science & AI services to see the operating depth behind the faculty. Seats close when the cohort is full. The best rooms always do.

Certification, Alumni Network & the MinervaDB University Standard

Each completed program carries the MinervaDB University Certificate of Advanced Completion — a credential that signals something rare in this industry: verified, hands-on advanced database training at principal-engineer depth, assessed through live lab work and an Architecture Council defense rather than a multiple-choice exam. Certificates are individually numbered and verifiable on request by employers and clients.

Graduates also join the MinervaDB University alumni network: a curated, invitation-only community of principal data architects, senior data scientists, CDOs, and CTOs across five continents. Alumni receive continued access to selected new research releases, priority invitations to faculty roundtables and masterclass previews, and preferential scheduling for MinervaDB and ChistaDATA consulting engagements. In a discipline where the hardest problems are solved by knowing whom to call, the room you gain may prove as valuable as the advanced database training itself.

About MinervaDB Inc. & ChistaDATA Inc.

MinervaDB Inc. is a vendor-neutral, full-stack database infrastructure company headquartered in the United States, trusted by 900+ enterprises for consulting, 24×7 emergency DBA coverage, remote DBA operations, and managed database services across PostgreSQL, MySQL, MariaDB, SQL Server, MongoDB, SAP HANA, and every major cloud platform. ChistaDATA Inc., its sister company, is the world's dedicated ClickHouse infrastructure operations firm, delivering consulting, support, and managed services on 100% open-source ClickHouse with zero vendor lock-in. MinervaDB University is the education arm of both practices — the channel through which two decades of production-hardened engineering doctrine becomes advanced database training for the leaders who need it most.

MinervaDB University advanced database training is delivered online worldwide. All programs are conducted in English over Zoom, with cohort windows scheduled for the Americas, EMEA, and APAC. For corporate procurement, W-9/vendor onboarding, and multi-seat invoicing, contact the MinervaDB University desk.