nedb

Yes! I plan to maintain it long-term! I will be rolling out some feature improvements and updates these few weeks. I still think Kong did a good job in crafting the product. I started using Insomnia in my previous company 3 years ago and our team loved it. What happened recently felt a little bit like the Unity fiasco (of course, in a much much smaller scale). Though as a user I would say Kong had taken a bad turn, as a dev I'm still grateful to them for open-sourcing such a fantastic product. One of the reasons I forked Insomnia was because it uses React & Electron, both of which I'm quite familiar with. And I think many parts of Insomnia are quite nicely written overall (but unfortunately things like nedb that was used is no longer maintained https://github.com/louischatriot/nedb so it's probably wise to swap out at some point)

At least for my needs, NeDB[0] is the best of both worlds for prototyping and early-stage production releases. It's human-readable, on-disk, greppable, still supports indexing and a subset of Mongo features while remaining serverless and in-memory. [0] https://github.com/louischatriot/nedb

Nicely done! I like the small codebase with no dependencies - I imagine it's easy to start using. Also appreciate the extensive query interface and documentation. It reminds me of NeDB in Node.js world, which has proven its worth to me on several occasions when I needed a simple JSON-based database for a small(ish) audience, with mostly read operations (which are served from memory). They're running for literally years with no issue at all. https://github.com/louischatriot/nedb

I've been using (and developing a fork of) NeDB [0] that does exactly what you describe: an in-memory database with append-only logs of changes for file-system persistence. On startup, and optionally at regular intervals, it "compacts" the database by reducing all events to a single JSON string. The README links to an article by @antirez, Redis Persistence Demystified [1]. It's been educational studying how it works. [0] https://github.com/louischatriot/nedb#persistence [1] http://oldblog.antirez.com/post/redis-persistence-demystifie...

I'm curious why NeDB wouldn't suffice. https://github.com/louischatriot/nedb

NeDB creator here. I'd like to know more about the issue you're describing, I've never heard about it and considering the test coverage I just don't see how it could happen. Could you post an issue on https://github.com/louischatriot/nedb with your environment details and how to reproduce this?

Also, I've used nedb and highly recommend it. It's fast and comprehensive. https://github.com/louischatriot/nedb

Is this the same Nedb? https://github.com/louischatriot/nedb/ Looks like a pretty nice project.

I use custom node.js scripts with these libraries: * request - https://github.com/mikeal/request * async - https://github.com/caolan/async * cheerio - https://github.com/cheeriojs/cheerio * nedb - https://github.com/louischatriot/nedb

you may ship your app with any database you want. Easiest to use is a pure-JS datastore, like https://github.com/louischatriot/nedb or sqlite. I prefer NeDB, it should work just fine for <= 1GB of data. If you want to use a non-embedded database, you have to build your own installer, though. The solutions offered by the chromium part (localStorage, indexedDB) could be worth a look, too. But i have no experience with them when using bigger amounts of data.

It might be interesting to persist snapshots to S3. It might be usable for small projects on Heroku/etc with ephemeral storage. It could be patched here (?) [1], but clearly there'd be a lot of issues with the long network call, how often to do it, how durable it really is, etc. 1: https://github.com/louischatriot/nedb/blob/b1abd34384cefea16...

I agree with the OP but I still think the power of algorithms and datastructures should not be understated, as they power most of the software everyone (including "organizational" coders) use, e.g. databases. For example, I'm writing a pure JS database (https://github.com/louischatriot/nedb), and using indexing I was able to speed it up hundreds fold. That's clearly not something I could have done without knowing about self-balancing binary search trees. I also think that knowing algorithms does make you a better programmer, even if you don't use them on a daily basis.