LNAV Reviews

Materialize Reviews

LNAV mentions (61)

• ht: Headless Terminal

  As others have kinda alluded to, it could be useful for testing TUI applications. I develop a logfile viewer for the terminal (https://lnav.org) and have a similar application[1] for testing, but it's a bit flaky. It produces/checks snapshots like [2]. I think the problems I run into are more around different versions of ncurses producing slightly different outputs. [1] - - Source: Hacker News / 6 days ago

• Ask HN: Interesting TUIs (text user interfaces), maybe forgotten ones?

  The Logfile Navigator (https://lnav.org) is a log file viewer/merger/tailer for the terminal. It has some advanced UX features, like showing previews of operations and displaying context sensitive help. For example, the preview for filtering out logs by regex is to highlight the lines that will be hidden in red. This can make crafting the right regex a bit easier since the preview updates as you type. lnav... - Source: Hacker News / about 1 month ago

• Angle-grinder: Slice and dice logs on the command line

  See https://lnav.org for a powerful mini-ETL CLI power tool; it embeds SQLite, supports ~every format, has great UX and easily handles a few million rows at a time. - Source: Hacker News / about 1 month ago

• Toolong: Terminal application to view, tail, merge, and search log files

  The code base seems like a good reference as a small Python project. My fav option in this class of apps: https://lnav.org/ It lets you use journalctl with pipes as requested here: https://github.com/Textualize/toolong/issues/4. - Source: Hacker News / 4 months ago

• Logdy.dev – web based logs viewer UI for local development environment

  For local development, I cannot recommend lnav[1] enough. Discovering this tool was a game changer in my day to day life. Adding comments, filtering in/out, prettify and analyse distribution is hard to live without now. I don't think a browser tool would fit in my workflow. I need to pipe the output to the tool. [1] https://lnav.org/. - Source: Hacker News / 4 months ago

Materialize mentions (65)

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  To fully leverage the data is the new oil concept, companies require a special database designed to manage vast amounts of data instantly. This need has led to different database forms, including NoSQL databases, vector databases, time-series databases, graph databases, in-memory databases, and in-memory data grids. Recent years have seen the rise of cloud-based streaming databases such as RisingWave, Materialize,... - Source: dev.to / 4 months ago

• We Built a Streaming SQL Engine

  Some recent solutions to this problem include Differential Dataflow and Materialize. It would be neat if postgres adopted something similar for live-updating materialized views. https://github.com/timelydataflow/differential-dataflow. - Source: Hacker News / 8 months ago

• Ask HN: Who is hiring? (October 2023)

  Materialize | Full-Time | NYC Office or Remote | https://materialize.com Materialize is an Operational Data Warehouse: A cloud data warehouse with streaming internals, built for work that needs action on what’s happening right now. Keep the familiar SQL, keep the proven architecture of cloud warehouses but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that... - Source: Hacker News / 8 months ago

• Ask HN: Who is hiring? (June 2023)

  Materialize | EM (Compute), Senior PM | New York, New York | https://materialize.com/ You shouldn't have to throw away the database to build with fast-changing data. Keep the familiar SQL, keep the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. That is Materialize, the only true SQL... - Source: Hacker News / about 1 year ago

• Ask HN: Who is hiring? (April 2023)

  Materialize | NY, NY | https://materialize.com/ The Cloud Database for Fast-Changing Data. We put a streaming engine in a database, so your team can build real-time data products without the cost, complexity, and development time of stream processing. Cloud team openings: https://grnh.se/0ad6ab6b4us Senior PM openings: https://grnh.se/415c267f4us. - Source: Hacker News / about 1 year ago