Update README.md

README.md

@@ -8,49 +8,47 @@ https://www.rust-lang.org)
 
 A _full-text search database_ using a key-value store internally.
 
-It uses [RocksDB](https://github.com/facebook/rocksdb) like a classic database, to store documents and internal data. The key-value store power allow us to handle updates and queries with small memory and CPU overheads.
+It uses [RocksDB](https://github.com/facebook/rocksdb) as a built-in database, to store documents and internal data. The key-value store power allow 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 informations on the engine, it describes the whole process of generating updates and handling queries.
+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.
 
-We will be proud if you send pull requests to help us grow this project, you can start with [issues tagged "good-first-issue"](https://github.com/Kerollmops/MeiliDB/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) to start !
+We will be proud if you submit pull requests. It will help to help to grow this project, you can 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 a good start!
 
-At the moment this is a library only, this means that binaries are not part of this repository but since I'm still nice I have made some examples for you in the `examples/` folder that works with the data located in the `misc/` folder.
+At the moment this project is only a library. It means that it's not prividing yet any binaries. To get started, we provided  some examples in the `examples/` folder that are made to work with the data located in the `misc/` folder.
 
-In a near future MeiliDB we be a binary like any database: updated and queried using some kind of protocol. It is the final goal, [see the milestones](https://github.com/Kerollmops/MeiliDB/milestones). MeiliDB will just be a bunch of network and protocols functions wrapping the library which itself will be published to https://crates.io, following the same update cycle.
+In a near future MeiliDB, we will provide a binary to execute this project as database, so you will be able to update and query it using a protocol. This will be our final goal, [see the milestones](https://github.com/Kerollmops/MeiliDB/milestones). At the end, MeiliDB will be a bunch of network protocols, and wrappers. We will publish the entire project on https://crates.io, following our usual update cycle.
 
 
 
 ## Performances
 
-_these informations have been made with a version dated of october 2018, we must update them_
+_these information are outdated  (October 2018) It will be updated soon_
 
-We made some tests on remote machines and found that we can handle with a dataset of near 280k products, on a server that cost 5$/month with 1vCPU and 1GB of ram and on the same index and with a simple query:
+We made some tests on remote machines and found that MeiliDB easily handles a dataset of near 280k products, on a $5/month server with a single vCPU and 1GB of RAM, running the same index, with a simple query:
 
-- near 190 users with an average response time of 90ms
-- 150 users with an average response time of 70ms
-- 100 users with an average response time of 45ms
+- near 190 concurrent users with an average response time of 90ms
+- 150 concurrent users with an average response time of 70ms
+- 100 concurrent users with an average response time of 45ms
 
-Network is mesured, servers are located in amsterdam and tests are made between two different datacenters.
+Servers were located in Amsterdam and tests were made between two different locations.
 
 ### 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 work with an index like most of the search engines.
+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
 ```
 
-Once the command finished indexing the database should have been saved under the `test.mdb` folder.
+Once the command is executed, the index should be in the `test.mdb` folder.
 
-Now you can easily run the `query-database` example to check what is stored in it.
+You are now able to run the `query-database` example, to play with MeiliDB.
 
 ```bash
 cargo run --release --example query-database -- test.mdb