Cursor Reviews

Apache Parquet Reviews

Cursor mentions (9)

• As SpaceX deal looms, Cursor partners with Chainguard to secure open-source dependencies in AI-built code

  Cursor has spent the past week in headlines after confirming a partnership with SpaceX that could eventually lead to a $60 billion acquisition. The deal, for now, centres on training more capable coding models using SpaceX’s compute infrastructure. - Source: dev.to / 5 days ago

• How to Get Your First Tool Online

  The step up from there is an editor with a built-in agent like Cursor, Google Antigravity, Windsurf, or VS Code with a coding extension. These are code editors with an AI agent living inside them, and the difference is the responsible party for getting things from place to place. Instead of the software creator shuttling code between windows, the AI agent edits the project files directly and runs the GitHub and... - Source: dev.to / 16 days ago

• I almost credited llms.txt for a Google AI Mode win. Then I read what Google actually says.

  Where llms.txt genuinely gets read is a different layer: coding and agent tooling — Cursor, Claude Code, GitHub Copilot, Windsurf — pulling a documentation site's pages with less token waste, plus emerging agent protocols like OpenAI's Agents SDK. That's real, and it's growing fast. - Source: dev.to / 16 days ago

• Tokens, Context, and Why Small AI Tasks Aren't Cheap

  If you don’t believe me, go to Google AI Studio, get you an API key, create a project, then open Cursor, add the key, add whatever model they have available to use, run a task and you will see how models like Gemini 3.5 or 2.5 Flash which gives you 5 Requests Per Minute and 20 Requests Per Day will scream at you with hitting a limit rate. - Source: dev.to / 23 days ago

• Use LLM for EDA licenses analysis

  Here is an example how to connect Prometheus DB to Cursor AI code editor. - Source: dev.to / 11 months ago

Apache Parquet mentions (31)

• Can you build observability ingestion on S3 alone — no Kafka, no disks, no coordination layer?

  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

• Zeroserve: A zero-config web server you can script with eBPF

  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

• What Are Table Formats and Why Were They Needed?

  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

• So, you know what? I just wasted 3 months of my life

  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

• Fix Slow Query: A Developer's Guide to Data Warehouse Performance

  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