By the end of this course, learners will:

• Install and configure SurrealDB for local and cloud environments.

• Write queries with SurrealQL for CRUD operations.

• Model data using tables, documents, and graph edges.

• Build real-time applications with live queries.

• Manage roles, authentication, and permissions.

• Deploy and scale SurrealDB in production environments.

Course Syllabus

Module 1: Introduction to SurrealDB

• Why SurrealDB? Advantages over SQL/NoSQL

• Core concepts and architecture

• Installation and setup

Module 2: SurrealQL Basics

• Creating databases and tables

• CRUD operations

• Filtering and sorting queries

Module 3: Data Modeling

• Document-style storage

• Relational links between tables

• Graph edges and traversals

Module 4: Real-Time Queries

• Subscriptions and live queries

• Building real-time dashboards

• Event-driven architecture

Module 5: Authentication & Security

• User authentication

• Roles and access permissions

• Multi-tenant database design

Module 6: Advanced SurrealQL

• Joins and nested queries

• Transactions and constraints

• Functions and stored procedures

Module 7: Integrations

• Using SurrealDB with REST and GraphQL APIs

• Frontend integrations (React, Svelte, Vue)

• Backend frameworks (Node.js, Go, Python)

Module 8: Deployment

• Running SurrealDB in Docker

• Kubernetes deployment

• Cloud scaling and monitoring

Module 9: Real-World Projects

• Chat application with live queries

• IoT sensor data storage and analytics

• Social graph with user relationships

Module 10: Best Practices

• Schema design strategies

• Performance optimization

• Backup and disaster recovery

Learners will receive a Certificate of Completion from Uplatz, validating their expertise in SurrealDB and multi-model database management. This certificate demonstrates readiness for roles in backend development, data engineering, and real-time app development.

SurrealDB skills prepare learners for roles such as:

• Backend Developer (Database-focused)

• Full-Stack Developer (SurrealDB integration)

• Database Engineer

• Real-Time Application Developer

• Cloud Data Architect

SurrealDB is increasingly adopted in web apps, IoT, real-time analytics, and graph-powered platforms, making it a valuable and future-oriented skill.

Interview Questions & Answers

1. What is SurrealDB?
   SurrealDB is a multi-model database combining SQL, document, and graph capabilities in one engine.

2. What query language does SurrealDB use?
   It uses SurrealQL, which is SQL-like but extended for document and graph queries.

3. How does SurrealDB support real-time applications?
   It provides live queries that automatically push updates to clients when data changes.

4. What makes SurrealDB different from MongoDB or PostgreSQL?
   Unlike MongoDB (document-only) or PostgreSQL (relational), SurrealDB natively supports relational + document + graph models in one.

5. What are graph edges in SurrealDB?
   Edges represent relationships between records, enabling graph queries across data.

6. How does authentication work in SurrealDB?
   It supports user authentication, roles, and permission-based access for fine-grained security.

7. What is a live query in SurrealDB?
   A query that stays open and streams real-time updates when underlying data changes.

8. Can SurrealDB be integrated with frontend frameworks?
   Yes, it integrates with React, Vue, Svelte, and others through APIs.

9. Does SurrealDB support transactions?
   Yes, SurrealDB supports ACID transactions, ensuring data consistency.

10. Where is SurrealDB commonly used?
    In real-time applications, IoT platforms, analytics dashboards, and graph-based apps.