Slicing Pie VS OctoSQL

You could try https://slicingpie.com/, but in practice I found it burdensome. - Source: Hacker News / 6 months ago

Since we were new to one another, we used the Slicing Pie methodology and monitored one another for progress and reasonableness in their reporting of time spent. Once we realized that we were both consistently committed to the project, we did a static split of equity and were on our way. Source: 11 months ago

Take a look at slicingpie.com as others have suggested. Source: 12 months ago

- ABSOLUTELY do vesting with one year cliff as others mentioned. Do NOT commit to 49% of the get-go just in case he has a change of heart in a few months... An alternative option is the Slicing Pie approach: https://slicingpie.com/ . Slicing pie is more complicated however it is fairer and will allow you to add more people. Source: 12 months ago

The slicing pie model might work (https://slicingpie.com/) for you depending on how far you are along. I am using this for a rev share project and we all feel it covered things pretty well. Source: 12 months ago

OctoSQL[0] or DuckDB[1] will most likely be much simpler, while going through 10 GB of JSON in a couple seconds at most. Disclaimer: author of OctoSQL [0]: https://github.com/cube2222/octosql. - Source: Hacker News / about 1 year ago

This is really cool! With their Postgres scanner[0] you can now easily query multiple datasources using SQL and join between them (i.e. Postgres table with JSON file). Something I strived to build with OctoSQL[1] before. It's amazing to see how quickly DuckDB is adding new features. Not a huge fan of C++, which is right now used for authoring extensions, it'd be really cool if somebody implemented a Rust extension... - Source: Hacker News / about 1 year ago

Congrats on the Show HN! It's great to see more tools in this area (querying data from various sources in-place) and the Lambda use case is a really cool idea! I've recently done a bunch of benchmarking, including ClickHouse Local and the usage was straightforward, with everything working as it's supposed to. Just to comment on the performance area though, one area I think ClickHouse could still possibly improve... - Source: Hacker News / over 1 year ago

SPyQL is really cool and its design is very smart, with it being able to leverage normal Python functions! As far as similar tools go, I recommend taking a look at DataFusion[0], dsq[1], and OctoSQL[2]. DataFusion is a very (very very) fast command-line SQL engine but with limited support for data formats. Dsq is based on SQLite which means it has to load data into SQLite first, but then gives you the whole breath... - Source: Hacker News / over 1 year ago

To add somewhat of a counterpoint to the other response, I've tried the Steampipe CSV plugin and got 50x slower performance vs OctoSQL[0], which is itself 5x slower than something like DataFusion[1]. The CSV plugin doesn't contact any external API's so it should be a good benchmark of the plugin architecture, though it might just not be optimized yet. That said, I don't imagine this ever being a bottleneck for the... - Source: Hacker News / over 1 year ago