Druid VS tauri

Apache Druid: Focused on real-time analytics and interactive queries on large datasets. Druid is well-suited for high-performance applications in user-facing analytics, network monitoring, and business intelligence.

Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in maintaining the freshness of results. The query in the streaming database focuses on recent data, making it suitable for continuous monitoring. Using streaming databases, you can run queries like finding the top 10 sold products where the “top 10 product list” might change in real-time.

https://github.com/apache/druid

It's always a question of tradeoffs.

The awesome-selfhosted project has a nice list of open-source analytics projects. It's really good inspiration to dig into these projects and find out about the technology choices that other open-source tools in the space have made.

Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s my analytical pipeline for Github stars data using Nifi, Kafka and Druid.

Apache Druid is part of the modern data architecture. It uses a special data format designed for analytical workloads, using extreme parallelisation to get data in and get data out. A shared-nothing, microservices architecture helps you to build highly-available, extreme scale analytics features into your applications.

Apache Druid

But then you realize there are other databases out there focused specifically on analytical use cases with lots of data and complex queries. Newcomers like ClickHouse, Pinot, and Druid (all open source) respond to a new class of problem: The need to develop applications using endpoints published on analytical queries that were previously confined only to the data warehouse and BI tools.

Datadog's product is a bit too close to Apache Druid to have named their design system so similarly.

From https://druid.apache.org/ :

> Druid unlocks new types of queries and workflows for clickstream, APM, supply chain, network telemetry, digital marketing, risk/fraud, and many other types of data. Druid is purpose built for rapid, ad-hoc queries on both real-time and historical data.

Maybe rare for someone to be seeking their first coding job at that age. But plenty of us are in our 50s or older and still coding up a storm. And not necessarily ancient tech or anything. My current project exposes analytics data from Apache Druid and Cassandra via Go microservices hosted in K8s.

Fortunately, it is super easy to build your own leveraging the binary distribution and existing docker.sh.

Hi, dear Tauri! Long time no see. I published my first post, Developing a Desktop Application via Rust and NextJS. The Tauri Way almost a year ago. Since then, Tauri has become stronger. I'm happy about that! And now, I am very pleased to make a useful contribution to the Tauri community. As a full-stack developer, I frequently face situations where I need to start a DB-based UI project as fast as possible. It's stressful if I need to start the project from 100% scratch. I prefer to keep some boilerplates on hand, which will save me time and nerves and will be the subject of this article.

Hey Thanks!

Just electron & vite. I might actually migrate off electron, Tauri (https://tauri.app/) seems to be getting more stable and it's gotten great reviews.

I think this is the boilerplate I used though https://github.com/cawa-93/vite-electron-builder.

Well the great thing about WebAssembly is that you can port QT or anything else to be at a layer below -- thanks to WebAssembly Interface Types[0] and the Component Model specification that works underneath that.

To over-simplify, the Component Model manages language interop, and WIT constrains the boundaries with interfaces.

IMO the problem here is defining a 90% solution for most window, tab, button, etc management, then building embeddings in QT, Flutter/Skia, and other lower level engines. Getting a good cross-platform way of doing data passing, triggering re-renders, serializing window state is probably the meat of the interesting work.

On top of that, you really need great UX. This is normally where projects fall short -- why should I use this solution instead of something like Tauri[2] which is excellent or Electron?

[0]: https://github.com/WebAssembly/component-model/blob/main/des...

[1]: https://github.com/WebAssembly/component-model/blob/main/des...

[2]: https://tauri.app/

Welcome to the 2nd episode of our series “Building with Tauri”, where we chat with developers who build amazing projects and products using Tauri.

Tauri seemed like the "thing" I should switch to because everybody loves Rust (heh), and because it ships significantly smaller apps.

First of all, I will be using npm as my package manager but feel free to use whatever you prefer. Find more info here.

Today I'm talking about Tauri! Do you know all the various tools that allow you to develop native applications starting from web languages? They often need an intermediate compilation, in the middle of which you end up encountering various problems not always transparent and directly solvable with a language mostly detached from native development. On the other hand, there's still the ease of developing attractive and easily usable interfaces, which are more difficult to develop with low level languages.

I think Tauri is the most established framework using that approach

https://tauri.app