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document the history of this project
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README.md

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@@ -297,7 +297,7 @@ Thanks to [Orlando Vazquez](https://github.com/orlandov),
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[Eric Fredricksen](https://github.com/grumdrig) and
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[Ryan Dahl](https://github.com/ry) for their SQLite bindings for node, and to mraleph on Freenode's #v8 for answering questions.
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This module was originally created by [Mapbox](https://mapbox.com/), then it was then taken over by [Ghost](https://ghost.org), but was then deprecated without prior notice, so that the original is no longer maintained. See [TryGhost/node-sqlite3](https://github.com/TryGhost/node-sqlite3)
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This module was originally created by [Mapbox](https://mapbox.com/), then it was taken over by [Ghost](https://ghost.org), but was then deprecated without prior notice, so that the original is no longer maintained. See [TryGhost/node-sqlite3](https://github.com/TryGhost/node-sqlite3)
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I still hope that it will eventually be taken over by a larger organization, but in the meantime, I'm trying to maintain this fork here.
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tools/benchmark-drivers/README.md

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| `@homeofthings/sqlite3` | ~47% | ~5.3μs/op | 3.3x more blocking than sync drivers |
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| `node:sqlite` | 100% | ~1.8μs/op | Blocks completely - all time is event loop time |
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Such metric shows the real cost: dependend on the operation, async drivers may even block the event loop **longer in total** for the same amount of work, even though they don't block it **completely** for the whole operation, like the sync drivers do. However, async drivers also do not always block the event loop **longer in total**:
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Such metric shows the real cost.
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For some operations, especially on very fast operations lasting only a few microseconds, async drivers **may** even block the event loop **longer in total**, even though they don't block it **completely** for the whole operation, like the sync drivers do. Here, for example, even for very short operations, the event loopis is less burdened by the async driver:
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```
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--- inserting rows individually ---
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### Long Running Query Performance
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With such a small amount of data we are currently using, it's not so easy to simulate longer running queries. That's why I tried it here using simple aggregation.
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With such a small amount of data we are currently using for this benchmark, it's not so easy to simulate longer running queries. That's why I tried it here using simple aggregation.
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Aggregate functions (COUNT, SUM, AVG, MIN, MAX) with WHERE clauses show even more dramatic async advantages:
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