What You'll Cover
This opening section equips you with the conceptual background needed for the rest of the workshop. By the end you will understand the OCI services involved, the role of MySQL HeatWave as a unified data platform, and how MySQL Studio provides a single browser-based workspace for SQL, AI chat, and notebooks.
OCI Cloud Basics
Regions, compartments, VCNs, and the services used throughout this lab — Compute, Networking, Object Storage, and the MySQL Database Service.
MySQL HeatWave
A single managed service combining OLTP, real-time analytics, Lakehouse, AutoML, and GenAI — no ETL, no separate engines.
MySQL Studio
The new browser-based workspace in OCI: SQL editor, AI-assisted chat, Jupyter-compatible notebooks, and project-based organization — all in one place.
OCI & MySQL HeatWave at a Glance
MySQL HeatWave is a fully managed cloud database service available on OCI, AWS, and Azure. It extends the MySQL DB System with a massively parallel, in-memory HeatWave Cluster that accelerates analytics, machine learning, and generative AI workloads — all without moving data out of the database.
Key architectural highlights: the HeatWave Cluster stores data in a hybrid columnar format in memory, enabling efficient analytical processing alongside the InnoDB row-store used for OLTP. Query offloading is automatic — the optimizer decides at runtime whether to execute on InnoDB or HeatWave. The Autopilot system provides ML-driven advisors for provisioning, data placement, query optimization, and error recovery.
MySQL HeatWave: One Service, Five Workloads
Unlike traditional cloud database stacks that require separate services for each workload type, MySQL HeatWave consolidates transactions, analytics, machine learning, generative AI, and lakehouse queries into a single managed service. This eliminates ETL pipelines, reduces operational complexity, and lowers cost.
| Capability | What It Does | Key Feature |
|---|---|---|
| OLTP | Transactional workloads on InnoDB with Enterprise Edition security | Group Replication, High Availability across 3 ADs |
| Analytics | Real-time OLAP on transactional data — no ETL duplication | Hybrid columnar engine, auto query offloading |
| AutoML | Build, train, and explain ML models in-database | ML_TRAIN, ML_PREDICT_TABLE, NL2ML |
| GenAI | In-database LLMs, vector store, RAG, and NL2SQL | ML_RAG, ML_GENERATE, HeatWave Chat |
| Lakehouse | Query structured, semi-structured, and unstructured data in Object Storage | Auto Parallel Load, Delta Lake support |
MySQL HeatWave GenAI
HeatWave GenAI is the core technology we'll leverage throughout this workshop. It provides integrated, automated, and secure generative AI capabilities directly within the database — no separate vector database, no external LLM orchestration, and no data movement required.
The beauty of HeatWave GenAI is that the entire RAG pipeline — document
ingestion, chunking, embedding generation, vector storage, similarity
search, prompt augmentation, and LLM inference — is orchestrated
through standard SQL calls. A single CALL sys.ML_RAG()
invocation handles retrieval-augmented generation end to end.
Key SQL routines you'll use: sys.ML_RAG()
for RAG queries, sys.ML_GENERATE() for content
generation, sys.ML_EMBED_ROW() for single-row
embeddings, sys.heatwave_load() for ingesting documents
into the vector store, and sys.NL_SQL() for
natural-language-to-SQL conversion.
MySQL Studio: Your Workshop Workspace
MySQL Studio is the browser-based environment where you'll spend most of this workshop. It was designed to lower the barrier to entry for working with MySQL HeatWave's advanced capabilities by unifying SQL editing, AI-assisted chat, and Jupyter-compatible notebooks in a single project-based workspace.
Studio connects directly to your MySQL DB System in OCI. All artifacts are organized into projects: SQL scripts, chat sessions, notebooks, and supporting files are stored together and automatically saved. This means you can switch between writing SQL, chatting with your data, and running Python analysis without leaving the browser.
SQL Editor
Write and run SQL with schema browsing, syntax highlighting, Explain Plan visualization, and results rendered as tables or charts. Natural Language to SQL converts plain English into executable queries.
AI Chat
RAG-enabled conversations where you can select vector stores and ask questions grounded in your proprietary documents. "Ask Oracle" provides contextual help for SQL and database topics.
Notebooks
Jupyter-compatible notebooks with Python, SQL, and Ibis DataFrame support. Ready-to-run guides cover AutoML, Lakehouse patterns, RAG workflows, and interactive visualizations.
Supported LLMs & Embedding Models
HeatWave GenAI supports both in-database LLMs (running directly on HeatWave nodes) and external models accessed via OCI Generative AI Service or Amazon Bedrock. Here are the key models available as of late 2025:
| Model | Type | Context | Notes |
|---|---|---|---|
llama3.2-3b-instruct-v1 | In-DB LLM | Default | Default LLM for content generation |
llama3.1-8b-instruct-v1 | In-DB LLM | 8B params | Higher quality, more compute |
mistral-7b-instruct-v3 | In-DB LLM | 7B params | Alternative in-database option |
| Cohere / Meta via OCI GenAI | External | Varies | Pre-trained foundational models, VLMs |
multilingual-e5-small | Embedding | Default | Default embedding model for vector store |
Workshop tip: GenAI features are available at no additional cost for MySQL HeatWave users, including on the HeatWave.Free shape. For this workshop we'll primarily use the default in-database LLM and embedding model.
Workshop Flow Preview
Here's what you'll build across the three sections:
What You Should Be Ready For
After completing this introduction you should understand:
- The OCI services involved in this workshop (MySQL Database Service, Object Storage, Networking)
- How MySQL HeatWave unifies OLTP, analytics, ML, GenAI, and Lakehouse in a single service
- The role of HeatWave GenAI — in-database LLMs, vector store, RAG, and NL2SQL
- What MySQL Studio is and how its three modalities (SQL, Chat, Notebooks) work together
- Where to click and what resources are available for the hands-on labs ahead