Fundamentals of Database Systems by Elmasri and Navathe is one of the most widely used textbooks for database courses globally. Official presentation slides are typically distributed by the publisher, Pearson, to verified instructors. 📂 Official PPT Resources

Chapter 2: Database System Concepts and Architecture – Focuses on data models, schemas, and instances.

Author Websites: Often, the authors provide supplementary materials for instructors that find their way into the public domain for student use. Tips for Studying from These Slides

: Providing users with a conceptual view that hides the complexities of physical storage. Theoretical and Conceptual Frameworks Chapter 1: Introduction

  1. Lecture Notes: The slides provide detailed lecture notes that summarize the key concepts and ideas in each chapter.
  2. Figures and Illustrations: The slides include figures and illustrations that help to clarify complex concepts and data models.
  3. Examples and Case Studies: The slides provide examples and case studies that illustrate the application of database systems in real-world scenarios.
  4. Exercises and Quizzes: The slides include exercises and quizzes that can be used by instructors to assess student understanding.

Focuses on Normalization. You’ll find slides explaining how to eliminate data redundancy using: First Normal Form (1NF) Second Normal Form (2NF) Third Normal Form (3NF) Boyce-Codd Normal Form (BCNF) 5. Transaction Processing & Recovery (Chapters 20–22)

Why Scribbler?

AI Without the Infrastructure

Scribbler runs AI models directly in your browser using WebGPU. No servers to manage, no APIs to pay for, no data leaving your device.

100% Private

All AI runs on your device. Your data never leaves the browser — no server, no tracking.

Zero Setup

No backend, no install, no npm, no Python. Open a URL and start running AI instantly.

WebGPU Accelerated

Leverages WebGPU for near-native performance on LLMs, image generation, and ML inference.

Load Any Library

Dynamically import TensorFlow.js, ONNX Runtime, Transformers.js, Plotly, and more from CDNs.

Share & Collaborate

Save notebooks as .jsnb files, share via URL, or push directly to GitHub.

Interactive Notebooks

Mix JavaScript, HTML, CSS, and Markdown in live cells. See AI output as you code.

AI Meets the Browser

WebGPU and JavaScript are unlocking a new era of on-device AI — accessible to everyone, everywhere.

0
%

Client-Side

0
servers

Required

0
+

AI Examples

0
sec

To First Output

How It's Different

Not Another Cloud Notebook

No Python. No backend. No GPU setup. Scribbler runs entirely in your browser — everything stays on your device.

No Python Required No Backend Needed No GPU Setup Runs Locally
Scribbler Google Colab Backend / Server Cloud APIs
Language JavaScript Python Python / Node / etc. Any
Runs On Your browser Google servers Your server / cloud VM Provider's cloud
Setup Time None Google login Install + configure API keys + billing
GPU Required WebGPU auto Runtime allocation CUDA / drivers Provider-managed
Data Privacy Never leaves device Sent to Google On your infra Sent to provider
Cost Free forever Free tier + paid GPU Server costs Per-request billing
Works Offline Yes
Live Demo

WebNN & ONNX
Right in Your Browser

Run Stable Diffusion, LLM chat, and text-to-speech directly on your device using WebNN and ONNX Runtime Web. No downloads, no cloud, no API keys — your browser's GPU does all the work.

  • Image Generation — Stable Diffusion via WebNN + ONNX Runtime
  • LLM Chat — Converse with language models on-device
  • Text to Speech — Kokoro TTS running entirely client-side
Open Full Demo
scribbler.live/webnn-sample
What Can You Build?

Use Cases

From generating images to running LLMs to crunching data — all in the browser with no infrastructure.

See what others are building

Image Generation

Run Stable Diffusion and other diffusion models directly in the browser via WebGPU.

Try It

Highlights

  • Text-to-image generation on-device.
  • No API keys or cloud costs.
  • Experiment with prompts interactively.
  • Share generated images and notebooks.

LLMs in Browser

Chat with Llama, Phi, Gemma and other LLMs locally using WebLLM — fully private.

Try It

Highlights

  • Run open-source LLMs on-device.
  • Build chat UIs and AI agents.
  • Text summarization and extraction.
  • Zero cost, zero latency to cloud.

Machine Learning

Train and run ML models with TensorFlow.js, Brain.js, and ONNX Runtime Web.

Try It

Highlights

  • Train neural networks in the browser.
  • Run pre-trained model inference.
  • Classification, regression, clustering.
  • Visualize training loss and metrics.

Data Analysis & Visualization

Analyze datasets and create interactive charts with Plotly, D3, and built-in tools.

Try It

Highlights

  • Interactive Plotly and D3 charts.
  • Load CSV, JSON, and API data.
  • Statistical analysis and transforms.
  • Export visualizations as HTML.
Scribbler Hub Scribbler Examples

Start running AI in your browser now.

No login, no download, no subscription. Just open the app and run LLMs, generate images, or visualize data — instantly.

Launch Scribbler

For enterprise use and partnerships reach out to us.

Elmasri Navathe Fundamentals Of Database Systems Ppt |best|

Fundamentals of Database Systems by Elmasri and Navathe is one of the most widely used textbooks for database courses globally. Official presentation slides are typically distributed by the publisher, Pearson, to verified instructors. 📂 Official PPT Resources

Chapter 2: Database System Concepts and Architecture – Focuses on data models, schemas, and instances.

Author Websites: Often, the authors provide supplementary materials for instructors that find their way into the public domain for student use. Tips for Studying from These Slides

: Providing users with a conceptual view that hides the complexities of physical storage. Theoretical and Conceptual Frameworks Chapter 1: Introduction

  1. Lecture Notes: The slides provide detailed lecture notes that summarize the key concepts and ideas in each chapter.
  2. Figures and Illustrations: The slides include figures and illustrations that help to clarify complex concepts and data models.
  3. Examples and Case Studies: The slides provide examples and case studies that illustrate the application of database systems in real-world scenarios.
  4. Exercises and Quizzes: The slides include exercises and quizzes that can be used by instructors to assess student understanding.

Focuses on Normalization. You’ll find slides explaining how to eliminate data redundancy using: First Normal Form (1NF) Second Normal Form (2NF) Third Normal Form (3NF) Boyce-Codd Normal Form (BCNF) 5. Transaction Processing & Recovery (Chapters 20–22)