# MeiliDB

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A _full-text search database_ using a key-value store internally.

It uses [RocksDB](https://github.com/facebook/rocksdb) as the internal key-value store. The key-value store allows us to handle updates and queries with small memory and CPU overheads.

You can [read the deep dive](deep-dive.md) if you want more information on the engine, it describes the whole process of generating updates and handling queries or you can take a look at the [typos and ranking rules](typos-ranking-rules.md) if you want to know the default rules used to sort the documents.

We will be proud if you submit issues and pull requests. You can help to grow this project and start contributing by checking [issues tagged "good-first-issue"](https://github.com/Kerollmops/MeiliDB/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22). It is a good start!

The project is only a library yet. It means that there is no binary provided yet. To get started, you can check the examples wich are made to work with the data located in the `misc/` folder.

MeiliDB will be a binary in a near future so you will be able to use it as a database out-of-the-box. We should be able to query it using a [to-be-defined](https://github.com/Kerollmops/MeiliDB/issues/38) protocol. This is our current goal, [see the milestones](https://github.com/Kerollmops/MeiliDB/milestones). In the end, the binary will be a bunch of network protocols and wrappers around the library - which will also be published on [crates.io](https://crates.io). Both the binary and the library will follow the same update cycle.



## Performances

With a database composed of _100 353_ documents with _352_ attributes each and _3_ of them indexed.
So more than _300 000_ fields indexed for _35 million_ stored we can handle more than _2.8k req/sec_ with an average response time of _9 ms_ on an Intel i7-7700 (8) @ 4.2GHz.

Requests are made using [wrk](https://github.com/wg/wrk) and scripted to simulate real users queries.

```
Running 10s test @ http://localhost:2230
  2 threads and 25 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
    Latency     9.52ms    7.61ms  99.25ms   84.58%
    Req/Sec     1.41k   119.11     1.78k    64.50%
  28080 requests in 10.01s, 7.42MB read
Requests/sec:   2806.46
Transfer/sec:    759.17KB
```

### Notes

The default Rust allocator has recently been [changed to use the system allocator](https://github.com/rust-lang/rust/pull/51241/).
We have seen much better performances when [using jemalloc as the global allocator](https://github.com/alexcrichton/jemallocator#documentation).

## Usage and examples

MeiliDB runs with an index like most search engines.
So to test the library you can create one by indexing a simple csv file.

```bash
cargo run --release --example create-database -- test.mdb misc/kaggle.csv --schema schema-example.toml
```

Once the command is executed, the index should be in the `test.mdb` folder. You are now able to run the `query-database` example and play with MeiliDB.

```bash
cargo run --release --example query-database -- test.mdb -n 10 id title
```