Based on our record, Supabase seems to be a lot more popular than Apache Flink. While we know about 521 links to Supabase, we've tracked only 45 mentions of Apache Flink. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This tutorial explains how I improved my application's read performance using Postgres materialized views in Supabase. - Source: dev.to / 4 days ago
All examples in this blog are tested on Supabase, an open source backend-as-a-service (BaaS) platform that simplifies backend development for web and mobile applications. Supabase provides full support for Postgres databases. - Source: dev.to / 10 days ago
But relying on these safeguards isn't as simple as sprinkling BEGIN and COMMIT into your code. You still have to address challenges like race conditions, constraint violations, and mid-transaction failures across API layers. Supabase helps solve these issues by building on Postgres and handling the transaction logic directly at the database itself. It exposes the logic through streamlined interfaces that preserve... - Source: dev.to / 11 days ago
If you don't have an account, head over to supabase.com and sign up. Once you're in, create a new project. Give it a name, generate a secure database password, and choose a region. Your project will be ready in a couple of minutes. - Source: dev.to / 11 days ago
Instead of setting up a local Postgres instance, I decided to use Supabase because it provides a fully managed, hosted Postgres database out of the box, simplifying the setup time and database management. This allows us to focus entirely on writing and deploying the application code without worrying about infrastructure details. First, visit Supabase and create a free account if you don't have one yet. - Source: dev.to / 16 days ago
In the meantime, other query engine support is on the roadmap, including Apache Spark, Apache Flink, and others. - Source: dev.to / about 2 months ago
Many stream processing systems today still rely on local disks and RocksDB to manage state. This model has been around for a while and works fine in simple, single-tenant setups. Apache Flink, for example, uses RocksDB as its default state backend - state is kept on local disks, and periodic checkpoints are written to external storage for recovery. - Source: dev.to / 3 months ago
Because the hosted catalog is a standard JDBC catalog, tools like Spark, Trino, and Flink can still access your tables. For example:. - Source: dev.to / 3 months ago
I wrote a python based aircraft monitor which polls the adsb.fi feed for aircraft transponder messages, and publishes each location update as a new event into an Apache Kafka topic. I used Apache Flink โ and more specially Flink SQL, to transform and analyse my flight data. The TL;DR summary is I can write SQL for my real-time data processing queries โ and get the scalability, fault tolerance, and low latency... - Source: dev.to / 4 months ago
Continuous Learning: Leverage online tutorials from the official Flink website and attend webinars for deeper insights. - Source: dev.to / 5 months ago
Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Next.js - A small framework for server-rendered universal JavaScript apps
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
AppWrite - Appwrite provides web and mobile developers with a set of easy-to-use and integrate REST APIs to manage their core backend needs.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.