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Node.js
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Based on our record, Node.js seems to be a lot more popular than Apache Parquet. While we know about 921 links to Node.js, we've tracked only 31 mentions of Apache Parquet. 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.
Node >= 22 or higher installed on their local development machine. - Source: dev.to / about 2 months ago
TypeScript / Node.js: Excellent for building asynchronous backend systems that must stream text data smoothly to thousands of users simultaneously. - Source: dev.to / about 2 months ago
Because Node.js operates on a single-threaded asynchronous runtime, it is inherently vulnerable to processes that hog the CPU for too long. I absolutely cringe whenever I see developers blindly copy-pasting complex regular expressions from StackOverflow without actually testing their performance impact. - Source: dev.to / about 2 months ago
This tutorial walks you through setting up a simple Docker Compose project that serves two Node web servers over HTTPS using Caddy as a reverse proxy. You will learn how to use mkcert to generate wildcard certificates and the minimal configuration needed in the Caddyfile and docker-compose.yml to get it all working. - Source: dev.to / 3 months ago
Node.js: This is required for Hardhat. You can check if your terminal has it installed by running node -v. It will show a version number, if it is already available. If not, download the LTS version from https://nodejs.org/en, install it, then reopen your terminal and recheck to confirm successful installation. - Source: dev.to / 4 months ago
Apache Iceberg fits these requirements well. Iceberg stores data as immutable Apache Parquet files and adds them through atomic commits, so readers always see a consistent snapshot. A separate metadata layer prunes files by their statistics before the data itself is ever read, and those statistics can be extended to match an observability filtering profile. - Source: dev.to / 10 days ago
Depends on the domain. There's a bunch of sciences using large datasets served up efficiently using static file formats, e.g., https://zarr.dev/ and https://parquet.apache.org/. - Source: Hacker News / about 1 month ago
The data files themselves are still standard Parquet or ORC. The table format adds a metadata layer on top that gives those files the properties of a database table. - Source: dev.to / 2 months ago
The dataset is huge - in parquet conversion - it is total 9gb. And in raw PNG image nested folders - it is 67 gigabytes. Huge... - Source: dev.to / 4 months ago
The solution is to standardize on columnar formats like Apache Parquet. Parquet stores data in columns, not rows, which immediately enables column pruning. If a query is SELECT avg(price) FROM sales, the engine reads only the price column and ignores all others. This can reduce storage footprints by up to 75% compared to raw formats and is a cornerstone of modern analytics performance. - Source: dev.to / 8 months ago
VS Code - Build and debug modern web and cloud applications, by Microsoft
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
ExpressJS - Sinatra inspired web development framework for node.js -- insanely fast, flexible, and simple
Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.
Laravel - A PHP Framework For Web Artisans
Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.