Learn about best practices for using indexes in SQL, and how they can be used to speed up your queries, make your database faster, and improve your application’s performance.
0:00 Intro
0:05 Example database table
0:15 Example query
0:21 The problem with a full table scan
0:50 Using EXPLAIN ANALYZE
1:04 What is a SQL index?
1:17 How to create a single-column index
1:37 How to create a multi-column index
2:08 Optimizing our SQL query
2:31 Caveats of sql indexes
What’s an API gateway? It is a server that exposes internal service APIs to external client devices, using a protocol like HTTP.
The gateway also uses design patterns like REST and GraphQL to expose APIs, which allow clients to get and update data through servers with databases.
In this video, we will talk about API gateways, their use cases, and how they work with CDNs and DNSes to ensure fast and reliable user request handling.
How does Uber handle real-time ride-sharing for millions of users? In this video, we design an Uber-like system, focusing on core components like APIs, database structure, real-time communication with WebSockets applying the principles of Event Driven Architecture. Learn how ride requests are processed, drivers are matched, and real-time updates are sent—all using an event-driven architecture and technologies like Kafka. Perfect for system design interviews or understanding scalable application architecture.
Timestamps:
0:00 – Introduction
0:43 – Clarifying Requirements and Scope
1:35 – API Design and Key Endpoints
3:47 – Real-Time Communication with WebSockets
4:08 – Database Design: Relational vs. NoSQL
10:31 – Event-Driven Architecture
13:10 – Detailed Workflow Example
13:58 – Real-Time Updates During a Ride
14:10 – WebSocket Session Management
15:46 – High-Level System Overview
18:30 – Future Enhancements
n this video, we’ll break down Event Driven Architecture (EDA) pattern and dive into real-world case studies from Netflix and Uber, who leverage EDA to handle billions of events daily.
Learn how EDA decouples services, enabling scalable, flexible, and efficient systems. We’ll also cover key components like Event Producers and Event Consumers, along with advanced concepts such as Complex Event Processing. Discover the advantages of using EDA alongside other patterns like Service Mesh and Sidecar Pattern.
If you’re looking to build scalable, real-time systems, this is the perfect video for you! Don’t forget to subscribe for more in-depth software architecture insights.
Timestamps
00:00 – Introduction to Event-Driven Architecture
00:30 – The need for EDA in modern systems
01:48 – EDA components: Producers and Consumers
02:29 – Netflix and Uber: Real-world EDA use cases
04:21 – EDA, Service Mesh and Sidecar pattern
05:53 – Event Processing: Simple and Complex
07:30 – EDA Challenges
07:55 – EDA Tooling: Kafka, SQS and RabbitMQ
Last time we checked in on [Inkbox], he had made a 16-bit CPU in Excel. Impressive, but not really practical. Presumably, his latest project isn’t any more practical, but we suspect an 8-bit RISC CPU was easier to implement in Excel and probably runs faster, too. The new machine uses a stack architecture with a simplified instruction set of ten instructions. You can follow along with his Excel adventure in the video below.
If you think about it, you may decide that doing something like this in Excel is easy because you could just script it and use Excel as the user interface. That’s true, but that’s not how [Inkbox] does it. He won’t use scripts or IF statements in a cell. That makes things much harder.
If you are curious about what goes on in a CPU, this is worth watching, even if you don’t expect you’ll use it. If you really want to become a CPU designer, we’d suggest skipping Excel and go straight into Verilog, VHDL, or something similar that you could actually use.
Don’t get us wrong. Seeing it done in Excel can be very educational, but no one designs CPUs like this in practice.
I built an 8-bit RISC CPU inside of Excel. The Processor uses a custom RISC ISA that has only 10 instructions (making this a Super-RISC computer). The machine has only a single register, but is equipped with a stack to help in executing instructions. The greater computer system features 1KB of RAM and ROM each, and a 16x16px 64-color screen.
The RISC-CPU.xlsx file features an 8-bit RISC CPU running a 10 instruction ISA. The system has 1 register, a stack, 1KB RAM, 1KB ROM, and a 16×16 64-color display.
Translate an ambiguous problem statement into CONCRETE one.
Articulate design decisions THROUGHOUT the discussions.
Know the pros and cons of different approaches.
Get comfortable with white drawing tools.
Give mocks.
Hyper Aware of time management.
Think out loud.
Focus on broader tradeoffs rather than low level designs.
Today’s data landscape, spanning operational, streaming, lakehouse, and warehouse systems, grapples with the complexities of decentralization. Do you seek new approaches, tools, and solutions to address challenges in data discovery, management, governance, quality, and observability?
How about a visibility layer, or control plane, for the data distributed across your stack?
In this session, Shirshanka Das, founder of the open source DataHub Project, will describe how a control plane for data, powered by metadata, can simplify data discovery, foster team collaboration, and offer real-time observability into data assets.
This talk will cover:
The control plane for data and its role in the decentralized data stack
Using the open-source DataHub Project to implement the control plane for data
How data contracts help you define and enforce decentralized governance
How this helps reduce operational overhead and keep cloud costs down
Why the industry is gravitating towards these ideas—and why the DataHub Project is key
Dive into the world of e-commerce and uncover the cutting-edge technology that powers your online shopping experience! In this video, we explore the secret tech that ensures your orders are processed smoothly and efficiently. From advanced algorithms to innovative software solutions, discover how these technologies scale to meet the demands of millions of users worldwide. Whether you’re a tech enthusiast or an e-commerce professional, this video will provide you with valuable insights into the backbone of online retail. Don’t forget to subscribe to Code with Jay for more tech-savvy content!
The team I joined about a month ago is using cursor based pagination and it makes sense why after seeing this explanation. I appreciate the video!
About cursor based pagination, this video mentioned “it stays consistent even when records are added or deleted”, however this is wrong.
Let me give an example, imagine page size is 10, and you have 100 entries with id range from 1 to 100.
First page returns first 10 records (from 1 to 10) and return cursor on <=10, in the meantime rows with id 2 and 12 are deleted (2 is deleted first).
The user asks for the next page, in this case the database will return 11 and 13..21.
So note that you didn't include 12, but you included 2 which means the total result is inconsistent (at no point in time the database contained id 21 and 2 without id 12)
Miguel Grinberg’s response when someone asks how to deal with Python being such a slow language is that Python is by far the fastest to write, cleanest, more maintainable programming language known, and that a bit of a runtime performance penalty is a small price to pay when rewarded with significant productivity gains.
Based on my analysis I’m pleasantly surprised with the performance improvements Python has received in the last couple of years starting with Python 3.11, and I’m also frankly blown away by PyPy, which I expected to be only marginally faster than CPython and is instead running at or close to Node.js speeds. I’m definitely going to play more with PyPy going forward!
The next version of the Python-to-C translator will be a major release, with more tools than ever to speed up your code. Here’s how to try it now.
Cython is the most convenient way to bridge C and Python languages and tools in Python programs. Developers use it to write C extensions or wrap C libraries for use in Python. Now, a major new release is on the way. While it’s in early stages, Cython 3.1 adds powerful new type annotation features, and it includes compatibility with the free-threaded or “no-GIL” build of Python. It’s worth a spin, especially for developers who like to stay ahead of the curve.
Support for free-threaded Python
Python 3.13 introduced the first public, if experimental, “free-threaded” or “no-GIL” builds of the language, which we’ll call “3.13t.”
3.13t allows CPU-bound Python threads to run with true parallelism. As a project, it’s still in the early stages of development, so it’s only offered as an opt-in option. You have to specifically install the free-threaded build in order to use it.
Deno Land has petitioned the US Patent and Trademark Office to strip Oracle of its ownership of the JavaScript trademark, accusing Oracle of trademark abandonment and fraud.
Developers looking to continue working in the C and C++ programming languages amid the global push to promote memory-safe programming now have another option that doesn’t involve learning Rust.
Filip Pizlo, senior director of language engineering at Epic Games, has created his own memory-safe flavor of C and – because why not? – named it after himself.
Pizlo got in touch after seeing our report on TrapC – a memory-safe C-fork due for release next year.
Feature flagging has changed the paradigm of how backend developers can test and modify the things they build. With feature flags, we can enable and disable a feature or change the functionality of something on the fly with a single click (no need to redeploy).
In this tutorial, we will see how feature flags help us to enable and disable a feature/a part of code whenever we want from the UI, without the need to redeploy the whole code
We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.
We are a professional review site that has advertisement and can receive compensation from the companies whose products we review. We use affiliate links in the post so if you use them to buy products through those links we can get compensation at no additional cost to you.OkDecline
981 Comments
Tomi Engdahl says:
Top 7 Ways to 10x Your API Performance
https://www.youtube.com/watch?v=zvWKqUiovAM
Tomi Engdahl says:
SQLite vs PostgreSQL Performance
https://www.youtube.com/watch?v=VzQgr-TgBzc
PostgreSQL vs SQLite Performance Comparison.
0:00 Intro
0:37 SQLite vs PostgreSQL Comparison
3:49 Test Design
6:30 Implementation Overview
7:13 1st Test (INSERT – UPDATE – DELETE)
11:59 2nd Test (SELECT)
Tomi Engdahl says:
What is RPC? gRPC Introduction.
https://www.youtube.com/watch?v=gnchfOojMk4
Tomi Engdahl says:
API Pagination: Making Billions of Products Scrolling Possible
https://www.youtube.com/watch?v=14K_a2kKTxU
Tomi Engdahl says:
7 Must-know Strategies to Scale Your Database
https://www.youtube.com/watch?v=_1IKwnbscQU&t=13s
SQL indexing best practices | How to make your database FASTER!
https://www.youtube.com/watch?v=BIlFTFrEFOI
Learn about best practices for using indexes in SQL, and how they can be used to speed up your queries, make your database faster, and improve your application’s performance.
0:00 Intro
0:05 Example database table
0:15 Example query
0:21 The problem with a full table scan
0:50 Using EXPLAIN ANALYZE
1:04 What is a SQL index?
1:17 How to create a single-column index
1:37 How to create a multi-column index
2:08 Optimizing our SQL query
2:31 Caveats of sql indexes
Tomi Engdahl says:
What is an API Gateway?
https://www.youtube.com/watch?v=RbMxB_Cyx6A
What’s an API gateway? It is a server that exposes internal service APIs to external client devices, using a protocol like HTTP.
The gateway also uses design patterns like REST and GraphQL to expose APIs, which allow clients to get and update data through servers with databases.
In this video, we will talk about API gateways, their use cases, and how they work with CDNs and DNSes to ensure fast and reliable user request handling.
Some of their most common use cases are:
1. Authentication and Authorization
2. Request Transformation
3. Request Validation
4. Rate Limiting
5. Routing
6. Load Balancing
Tomi Engdahl says:
Uber System Design | Websockets and Event Driven Architecture
https://www.youtube.com/watch?v=2WYjtfRyHzQ
How does Uber handle real-time ride-sharing for millions of users? In this video, we design an Uber-like system, focusing on core components like APIs, database structure, real-time communication with WebSockets applying the principles of Event Driven Architecture. Learn how ride requests are processed, drivers are matched, and real-time updates are sent—all using an event-driven architecture and technologies like Kafka. Perfect for system design interviews or understanding scalable application architecture.
Timestamps:
0:00 – Introduction
0:43 – Clarifying Requirements and Scope
1:35 – API Design and Key Endpoints
3:47 – Real-Time Communication with WebSockets
4:08 – Database Design: Relational vs. NoSQL
10:31 – Event-Driven Architecture
13:10 – Detailed Workflow Example
13:58 – Real-Time Updates During a Ride
14:10 – WebSocket Session Management
15:46 – High-Level System Overview
18:30 – Future Enhancements
Tomi Engdahl says:
Unlock the Power of Event-Driven Architecture: How Netflix & Uber Handle Billions of Events
https://www.youtube.com/watch?v=hrvx8Nv9eQA
n this video, we’ll break down Event Driven Architecture (EDA) pattern and dive into real-world case studies from Netflix and Uber, who leverage EDA to handle billions of events daily.
Learn how EDA decouples services, enabling scalable, flexible, and efficient systems. We’ll also cover key components like Event Producers and Event Consumers, along with advanced concepts such as Complex Event Processing. Discover the advantages of using EDA alongside other patterns like Service Mesh and Sidecar Pattern.
If you’re looking to build scalable, real-time systems, this is the perfect video for you! Don’t forget to subscribe for more in-depth software architecture insights.
Timestamps
00:00 – Introduction to Event-Driven Architecture
00:30 – The need for EDA in modern systems
01:48 – EDA components: Producers and Consumers
02:29 – Netflix and Uber: Real-world EDA use cases
04:21 – EDA, Service Mesh and Sidecar pattern
05:53 – Event Processing: Simple and Complex
07:30 – EDA Challenges
07:55 – EDA Tooling: Kafka, SQS and RabbitMQ
Tomi Engdahl says:
IPC: To Share Memory Or To Send Messages
https://www.youtube.com/watch?v=Y2mDwW2pMv4
Tomi Engdahl says:
CICD Pipeline | System Design
https://www.youtube.com/watch?v=su3-fAEePs0&list=PLJq-63ZRPdBssWTtcUlbngD_O5HaxXu6k
In this video we will understand and design a CICD (Continuous Integration and Continuous Delivery) Pipeline. This is taken from Ex-Googler interview,
Tomi Engdahl says:
RISC CPU Lives In Excel
https://hackaday.com/2024/11/24/risc-cpu-lives-in-excel/
Last time we checked in on [Inkbox], he had made a 16-bit CPU in Excel. Impressive, but not really practical. Presumably, his latest project isn’t any more practical, but we suspect an 8-bit RISC CPU was easier to implement in Excel and probably runs faster, too. The new machine uses a stack architecture with a simplified instruction set of ten instructions. You can follow along with his Excel adventure in the video below.
If you think about it, you may decide that doing something like this in Excel is easy because you could just script it and use Excel as the user interface. That’s true, but that’s not how [Inkbox] does it. He won’t use scripts or IF statements in a cell. That makes things much harder.
If you are curious about what goes on in a CPU, this is worth watching, even if you don’t expect you’ll use it. If you really want to become a CPU designer, we’d suggest skipping Excel and go straight into Verilog, VHDL, or something similar that you could actually use.
Don’t get us wrong. Seeing it done in Excel can be very educational, but no one designs CPUs like this in practice.
I Built a BETTER CPU in Excel
https://www.youtube.com/watch?v=MNRKi7Rum_c
I built an 8-bit RISC CPU inside of Excel. The Processor uses a custom RISC ISA that has only 10 instructions (making this a Super-RISC computer). The machine has only a single register, but is equipped with a stack to help in executing instructions. The greater computer system features 1KB of RAM and ROM each, and a 16x16px 64-color screen.
The Excel SRISC CPU:
Excel 8-Bit RISC CPU
https://github.com/InkboxSoftware/excelRISC-CPU
The RISC-CPU.xlsx file features an 8-bit RISC CPU running a 10 instruction ISA. The system has 1 register, a stack, 1KB RAM, 1KB ROM, and a 16×16 64-color display.
Tomi Engdahl says:
System Design Explained | Why It’s Crucial for Tech Interviews & Real-World Success
https://www.youtube.com/watch?v=ABwZfwisPXo
How to Crack Any System Design Interview
https://www.youtube.com/watch?v=o-k7h2G3Gco
Translate an ambiguous problem statement into CONCRETE one.
Articulate design decisions THROUGHOUT the discussions.
Know the pros and cons of different approaches.
Get comfortable with white drawing tools.
Give mocks.
Hyper Aware of time management.
Think out loud.
Focus on broader tradeoffs rather than low level designs.
Tomi Engdahl says:
Building an open source control plane for data
https://www.youtube.com/watch?v=gTwho9ijc-8
Today’s data landscape, spanning operational, streaming, lakehouse, and warehouse systems, grapples with the complexities of decentralization. Do you seek new approaches, tools, and solutions to address challenges in data discovery, management, governance, quality, and observability?
How about a visibility layer, or control plane, for the data distributed across your stack?
In this session, Shirshanka Das, founder of the open source DataHub Project, will describe how a control plane for data, powered by metadata, can simplify data discovery, foster team collaboration, and offer real-time observability into data assets.
This talk will cover:
The control plane for data and its role in the decentralized data stack
Using the open-source DataHub Project to implement the control plane for data
How data contracts help you define and enforce decentralized governance
How this helps reduce operational overhead and keep cloud costs down
Why the industry is gravitating towards these ideas—and why the DataHub Project is key
Tomi Engdahl says:
Mastering Kafka with Node.js: Build a Seamless Order Creation System
https://www.youtube.com/watch?v=hsERcsA8WPY
Dive into the world of e-commerce and uncover the cutting-edge technology that powers your online shopping experience! In this video, we explore the secret tech that ensures your orders are processed smoothly and efficiently. From advanced algorithms to innovative software solutions, discover how these technologies scale to meet the demands of millions of users worldwide. Whether you’re a tech enthusiast or an e-commerce professional, this video will provide you with valuable insights into the backbone of online retail. Don’t forget to subscribe to Code with Jay for more tech-savvy content!
Tomi Engdahl says:
API Pagination: Making Billions of Products Scrolling Possible
https://www.youtube.com/watch?v=14K_a2kKTxU&t=103s
The team I joined about a month ago is using cursor based pagination and it makes sense why after seeing this explanation. I appreciate the video!
About cursor based pagination, this video mentioned “it stays consistent even when records are added or deleted”, however this is wrong.
Let me give an example, imagine page size is 10, and you have 100 entries with id range from 1 to 100.
First page returns first 10 records (from 1 to 10) and return cursor on <=10, in the meantime rows with id 2 and 12 are deleted (2 is deleted first).
The user asks for the next page, in this case the database will return 11 and 13..21.
So note that you didn't include 12, but you included 2 which means the total result is inconsistent (at no point in time the database contained id 21 and 2 without id 12)
Tomi Engdahl says:
Is Python really that slow? (hint: no)
https://blog.adafruit.com/2024/11/27/is-python-really-that-slow-hint-no/
Miguel Grinberg’s response when someone asks how to deal with Python being such a slow language is that Python is by far the fastest to write, cleanest, more maintainable programming language known, and that a bit of a runtime performance penalty is a small price to pay when rewarded with significant productivity gains.
Based on my analysis I’m pleasantly surprised with the performance improvements Python has received in the last couple of years starting with Python 3.11, and I’m also frankly blown away by PyPy, which I expected to be only marginally faster than CPython and is instead running at or close to Node.js speeds. I’m definitely going to play more with PyPy going forward!
https://blog.miguelgrinberg.com/post/is-python-really-that-slow
Tomi Engdahl says:
https://www.marktechpost.com/2024/11/29/andrew-ngs-team-releases-aisuite-a-new-open-source-python-library-for-generative-ai/
Tomi Engdahl says:
Python to C: What’s new in Cython 3.1
https://www.infoworld.com/article/3609676/python-to-c-whats-new-in-cython-3-1.html
The next version of the Python-to-C translator will be a major release, with more tools than ever to speed up your code. Here’s how to try it now.
Cython is the most convenient way to bridge C and Python languages and tools in Python programs. Developers use it to write C extensions or wrap C libraries for use in Python. Now, a major new release is on the way. While it’s in early stages, Cython 3.1 adds powerful new type annotation features, and it includes compatibility with the free-threaded or “no-GIL” build of Python. It’s worth a spin, especially for developers who like to stay ahead of the curve.
Support for free-threaded Python
Python 3.13 introduced the first public, if experimental, “free-threaded” or “no-GIL” builds of the language, which we’ll call “3.13t.”
3.13t allows CPU-bound Python threads to run with true parallelism. As a project, it’s still in the early stages of development, so it’s only offered as an opt-in option. You have to specifically install the free-threaded build in order to use it.
Tomi Engdahl says:
https://www.akamai.com/lp/api-security-power-of-n
Tomi Engdahl says:
USPTO petitioned to cancel Oracle’s JavaScript trademark
https://www.infoworld.com/article/3612364/uspto-petitioned-to-cancel-oracles-javascript-trademark.html
Deno Land has petitioned the US Patent and Trademark Office to strip Oracle of its ownership of the JavaScript trademark, accusing Oracle of trademark abandonment and fraud.
Tomi Engdahl says:
https://www.hackster.io/news/a-new-formula-for-a-risc-cpu-b6cb26a13c4c
Tomi Engdahl says:
Abstract, theoretical computing qualifications are turning teens off
BCS calls for digital literacy GCSE alongside Computer Science
https://www.theregister.com/2024/11/28/bcs_computer_science_gcse/
Tomi Engdahl says:
5 reasons Proxmox is better than Hyper-V for home lab enthusiasts
https://www.xda-developers.com/reasons-proxmox-is-better-than-hyper-v-for-home-lab-enthusiasts/
Tomi Engdahl says:
Advent of Code in Rust for the Rest of Us
https://blog.jetbrains.com/rust/2024/11/29/advent-of-code-in-rust-for-the-rest-of-us/
Tomi Engdahl says:
Rust haters, unite! Fil-C aims to Make C Great Again
It’s memory-safe, with a few caveats
https://www.theregister.com/2024/11/16/rusthaters_unite_filc/
Developers looking to continue working in the C and C++ programming languages amid the global push to promote memory-safe programming now have another option that doesn’t involve learning Rust.
Filip Pizlo, senior director of language engineering at Epic Games, has created his own memory-safe flavor of C and – because why not? – named it after himself.
Pizlo got in touch after seeing our report on TrapC – a memory-safe C-fork due for release next year.
Tomi Engdahl says:
How to Learn Python for JavaScript Developers [Full Handbook]
https://www.freecodecamp.org/news/learn-python-for-javascript-developers-handbook/
Tomi Engdahl says:
https://www.kdnuggets.com/exploring-pythons-ellipsis-more-than-just-syntax-sugar
Tomi Engdahl says:
How to Build a Flexible API with Feature Flags Using Open Source Tools
https://www.freecodecamp.org/news/build-a-flexible-api-with-feature-flags-using-open-source-tools/
Feature flagging has changed the paradigm of how backend developers can test and modify the things they build. With feature flags, we can enable and disable a feature or change the functionality of something on the fly with a single click (no need to redeploy).
In this tutorial, we will see how feature flags help us to enable and disable a feature/a part of code whenever we want from the UI, without the need to redeploy the whole code
Tomi Engdahl says:
https://thenewstack.io/warp-is-a-power-users-dream-terminal-for-linux/
Tomi Engdahl says:
https://www.howtogeek.com/things-i-wish-i-knew-when-i-first-learned-programming/
Tomi Engdahl says:
C just in time
https://news.ycombinator.com/item?id=42246209