Scaling up Your Database With ReadySet

Rate this content
Bookmark

The database can be one of the hardest parts of a web app to scale. Many projects end up using ad-hoc caching systems that are complex, error-prone, and expensive to build. What if you could drop in a ready-built caching system to enable better throughput and latency with no code changes to your application?


Join developers Aspen Smith and Nick Marino to see how you can change one line of config in your app and use ReadySet to scale up your query performance by orders of magnitude today.


Aspen Smith
Aspen Smith
Nick Marino
Nick Marino
33 min
12 Apr, 2023

Comments

Sign in or register to post your comment.

Video Summary and Transcription

ReadySet is a plug and play caching solution that improves database performance and query optimization. It supports scaling out to multiple nodes without additional load on the database and ensures real-time cache updates. ReadySet significantly speeds up queries and reduces query time, making it a game-changer for web applications. It is not designed for write-heavy applications but works best for read-heavy loads. Community feedback is encouraged, and a cloud version of ReadySet is available for production use.

1. Introduction to Scaling with ReadySet

Short description:

We're going to talk about scaling up your database with ReadySet. We'll explain the problem it solves and give a demonstration of its usage. Then we'll open it up for questions.

Hey, everybody. I'm Nick Marino. Hi, I'm Griffin Smith. And we're going to talk about scaling up your database with ReadySet. So just to summarize, we're going to start off and give kind of some background information, explain what the problem is that ReadySet is trying to solve, how it solves it. And then Griffin's going to give a demonstration that kind of shows how to use ReadySet with a real-world application and kind of gives you an idea of some of the performance benefits and features you can expect to see there. And finally, after that, we'll open it up for questions that any of you might have.

2. Introduction to ReadySet

Short description:

ReadySet is a caching system for MySQL and PostgreSQL that allows you to create caches for individual SQL queries on the fly, resulting in significant speed improvements. The problem it solves is the difficulty of scaling a database when your application grows in popularity. Starting with a single server relational database is common, but as your idea becomes successful, the database struggles to keep up. Using MySQL or Postgres initially is convenient, but when scaling limits are reached, it becomes a challenging problem to solve. The critical point for user experience in a web application is read performance, with loading a web page feeling instantaneous at around 200 milliseconds. To scale up database reads, you can optimize queries, use read replicas, or consider other options.

All right. So first off, what is ReadySet? So you know, if you look at the ReadySet website, it says it's a caching system for MySQL and PostgreSQL, which is true. And when I first looked at the website, though, I kind of saw that and thought, oh, maybe it's just a wrapper around, you know, Redis or Memcached or a clone of some kind of existing popular caching system. So you know, it's something like a cool, useful product, but maybe not anything that revolutionary. It does turn out it's actually much more than that. It allows you to quickly and easily create caches for individual SQL queries on the fly with no changes to your application needed, other than maybe like a config change or two. And, you know, I don't want to spoil too much of the demonstration later, but in one of the queries that we've benchmarked, we see something like a 25,000 speedup. So that's pretty exciting, I think. But before we get into all that, let's discuss the problem. So I think this quote kind of encapsulates the problem we're trying to solve pretty well, so I'll just read it aloud. The data access layer of a million dollar idea starts out as a single server relational database. You're hardly worried about scale issues, you have an application to write. However, if your million dollar idea ends up being worth even 100,000, you'll likely find your database struggling to keep up with the scale. And this is certainly a story that I'm personally familiar with. I know a lot of people out there probably are as well. When you're starting a start-up or website and you're at a very early stage, you don't really have the time and resources to build something using the latest fancy, no-SQL, scalable fad of the day and there's nothing wrong with using MySQL or Postgres. They're free, they're very popular, they're easy to use. And when you're just trying to get a simple initial version of something, a minimum viable product, a prototype, whatever you want to call it, you don't want to spend too much time dealing with really complex, sophisticated scaling systems. You just want to get something that works. But, of course, if and when you do hit scaling limits in your database, it can be a pretty tricky problem to solve. And it's a good problem to have, but it often comes at a pretty critical point in the life of a website or an organization. So if we're sort of looking at the problem that we're running into here, I just want to sort of frame it very briefly. When you're scaling out a production web application, I think the first thing that you start to really care about as you sort of hit the scaling limits of a single database server is read performance. I think for most web applications, that's where sort of the critical point for user experience, there's this number that's quoted and there's some pretty extensive research that shows that loading a web page feels instantaneous at about 200 milliseconds. And that 200 milliseconds, most of the time you're spending is reading data out of your database. And so if you need to scale up those database reads, if you need to make those database reads faster, there are three sort of high-level main options that you're going to take there. You could spend a lot of time optimizing your queries. That can be as simple as adding indexes or something more involved. You could use a read replica to scale out the query throughput. So if you're getting a lot of queries, you could use read replicas to increase the number of queries you can handle.

Watch more workshops on topic

How to Solve Real-World Problems with Remix
Remix Conf Europe 2022Remix Conf Europe 2022
195 min
How to Solve Real-World Problems with Remix
Featured Workshop
Michael Carter
Michael Carter
- Errors? How to render and log your server and client errorsa - When to return errors vs throwb - Setup logging service like Sentry, LogRocket, and Bugsnag- Forms? How to validate and handle multi-page formsa - Use zod to validate form data in your actionb - Step through multi-page forms without losing data- Stuck? How to patch bugs or missing features in Remix so you can move ona - Use patch-package to quickly fix your Remix installb - Show tool for managing multiple patches and cherry-pick open PRs- Users? How to handle multi-tenant apps with Prismaa - Determine tenant by host or by userb - Multiple database or single database/multiple schemasc - Ensures tenant data always separate from others
Relational Database Modeling for GraphQL
GraphQL Galaxy 2020GraphQL Galaxy 2020
106 min
Relational Database Modeling for GraphQL
Top Content
WorkshopFree
Adron Hall
Adron Hall
In this workshop we'll dig deeper into data modeling. We'll start with a discussion about various database types and how they map to GraphQL. Once that groundwork is laid out, the focus will shift to specific types of databases and how to build data models that work best for GraphQL within various scenarios.
Table of contentsPart 1 - Hour 1      a. Relational Database Data Modeling      b. Comparing Relational and NoSQL Databases      c. GraphQL with the Database in mindPart 2 - Hour 2      a. Designing Relational Data Models      b. Relationship, Building MultijoinsTables      c. GraphQL & Relational Data Modeling Query Complexities
Prerequisites      a. Data modeling tool. The trainer will be using dbdiagram      b. Postgres, albeit no need to install this locally, as I'll be using a Postgres Dicker image, from Docker Hub for all examples      c. Hasura
Build a Full Stack React Native App with Oracle 23ai
React Summit 2024React Summit 2024
37 min
Build a Full Stack React Native App with Oracle 23ai
WorkshopFree
Doug Drechsel
Doug Drechsel
In this workshop, you will set up a local full-stack environment and create a React Native Mobile app that runs against that stack. 
Agenda:- Install Oracle 23ai Docker container- Build and run Parse Server with the new Oracle Storage Adapter - Build and run a Walking History React Native mobile app against the stack
Walking History is a React Native application that allows you to walk around New York City (or simulate that in a device emulator) and it tells you about the closest attraction or point of interest.


Building a Realtime App with Remix and Supabase
Remix Conf Europe 2022Remix Conf Europe 2022
156 min
Building a Realtime App with Remix and Supabase
Workshop
Jon Meyers
Jon Meyers
Supabase and Remix make building fullstack apps easy. In this workshop, we are going to learn how to use Supabase to implement authentication and authorization into a realtime Remix application. Join Jon Meyers as he steps through building this app from scratch and demonstrating how you can harness the power of relational databases!
Building a GraphQL-native serverless backend with Fauna
GraphQL Galaxy 2021GraphQL Galaxy 2021
143 min
Building a GraphQL-native serverless backend with Fauna
WorkshopFree
Rob Sutter
Shadid Haque
2 authors
Welcome to Fauna! This workshop helps GraphQL developers build performant applications with Fauna that scale to any size userbase. You start with the basics, using only the GraphQL playground in the Fauna dashboard, then build a complete full-stack application with Next.js, adding functionality as you go along.

In the first section, Getting started with Fauna, you learn how Fauna automatically creates queries, mutations, and other resources based on your GraphQL schema. You learn how to accomplish common tasks with GraphQL, how to use the Fauna Query Language (FQL) to perform more advanced tasks.

In the second section, Building with Fauna, you learn how Fauna automatically creates queries, mutations, and other resources based on your GraphQL schema. You learn how to accomplish common tasks with GraphQL, how to use the Fauna Query Language (FQL) to perform more advanced tasks.
Building GraphQL APIs With The Neo4j GraphQL Library
GraphQL Galaxy 2021GraphQL Galaxy 2021
175 min
Building GraphQL APIs With The Neo4j GraphQL Library
WorkshopFree
William Lyon
William Lyon
This workshop will explore how to build GraphQL APIs backed Neo4j, a native graph database. The Neo4j GraphQL Library allows developers to quickly design and implement fully functional GraphQL APIs without writing any resolvers. This workshop will show how to use the Neo4j GraphQL Library to build a Node.js GraphQL API, including adding custom logic and authorization rules.

Table of contents:
- Overview of GraphQL and building GraphQL APIs
- Building Node.js GraphQL APIs backed a native graph database using the Neo4j GraphQL Library
- Adding custom logic to our GraphQL API using the @cypher schema directive and custom resolvers
- Adding authentication and authorization rules to our GraphQL API

Check out more articles and videos

We constantly think of articles and videos that might spark Git people interest / skill us up or help building a stellar career

TypeScript and the Database: Who Owns the Types?
TypeScript Congress 2022TypeScript Congress 2022
27 min
TypeScript and the Database: Who Owns the Types?
Top Content
We all love writing types in TypeScript, but we often find ourselves having to write types in another language as well: SQL. This talk will present the choose-your-own-adventure story that you face when combining TypeScript and SQL and will walk you through the tradeoffs between the various options. Combined poorly, TypeScript and SQL can be duplicative and a source of headaches, but done well they can complement one another by addressing each other's weaknesses.
I Would Never Use an ORM
JSNation 2023JSNation 2023
29 min
I Would Never Use an ORM
Top Content
What's an ORM? An Object-Relational Mapping tool (ORM) is a library to map a SQL table to a Class. In most cases, ORMs force the users to structure their code to have Model objects that include both data access and business logic.
Once upon a time, I did several projects using ORMs as I followed the common belief that they would simplify the development and maintenance of projects. I was wrong. ORMs are often a hurdle to overcome for the most complex part of a project.
As the next stop of my journey, I recommended people use the native languages of their databases, e.g., SQL. This works great for the most part, but it creates quite a struggle: there is a lot of boilerplate code to write that can be pretty tedious. I was wrong, again.
Today I'm presenting you Platformatic DB.
Database Access on the Edge with Cloudflare Workers & Prisma
Node Congress 2022Node Congress 2022
31 min
Database Access on the Edge with Cloudflare Workers & Prisma
Edge functions are pushing the limit of serverless computing – but with new tools, come new challenges. Due to their limitations, edge functions don't allow talking to popular databases like PostgreSQL and MySQL. In this talk, you will learn how you can connect and interact with your database from Cloudflare Workers using the Prisma Data Proxy.
You can check the slides for Alex's talk here. 
Bring AI-Based Search to Your Web App
JSNation 2023JSNation 2023
31 min
Bring AI-Based Search to Your Web App
ChatGPT took the tech world by storm. Everyone talks about it, from your CTO to your hairdresser (at least my barber does). And there are many reasons why we should all be excited about it and many other AI/ML innovations.
But how do you bring them into your tech stack, your website/backend, to work with your data and provide AI-driven search and data augmentation?
There is a new generation of AI Native databases, which use deep learning models to find answers to natural language queries. We are talking about the ability to search through text, images, videos, DNA, or any unstructured data, all with a single query.
The rule of thumb: if there is an ML model, we can search through it.
Join me to learn about the foundation blocks (LLMs and vector embeddings, Vector Databases), how they all play together and most importantly - how you can build something yourself with open-source tech.
And, of course!!! There will be a live-coding demo, where I will take you through the experience of building an AI-based search – with Weaviate, an open-source Vector Database – and adding it to an app. Now the question... should this be done in Angular, React, Vue or just pure JS ;)
#MayTheDemoGodsBeWithUs
Remix Persistence With DynamoDB
Remix Conf Europe 2022Remix Conf Europe 2022
41 min
Remix Persistence With DynamoDB
Remix is the best React framework for working with the second most important feature of the web: forms. (Anchors are more important.) But building forms is the fun part: the tricky part is what happens when a web consumer submits a form! Not the client side validation logic but the brass tacks backend logic for creating, reading, updating, destroying, and listing records in a durable database (CRUDL). Databases can be intimidating. Which one to choose? What are the tradeoffs? How do I model data for fast queries? In this talk, we'll learn about the incredibly powerful AWS DynamoDB. Dynamo promises single-digit millisecond latency no matter how much data you have stored, scaling is completely transparent, and it comes with a generous free tier. Dynamo is a different level of database but it does not have to be intimidating.
Local-First Software With ElectricSQL
React Advanced Conference 2023React Advanced Conference 2023
29 min
Local-First Software With ElectricSQL
Local-first is a new paradigm for developing apps, where your components talk to a local embedded database and you get instant reactivity, multi-user sync and conflict-free offline support built in. ElectricSQL is a new, open-source, platform for local-first development from the inventors of CRDTs. This talk introduces local-first development and shows how you can develop real-world local-first apps today with React + ElectricSQL.