yottaStore VS bbolt

I'm building a database, and I'm working on the storage format. For each record I have a logical clock which increases by 1 every time there's a write operation on the record, and I would like to be able to compare the clocks of two writes to understand which happened first.

If you're curious to know more, the tree is used for rendezvous based routing, as used by my datastore. I'm doing machine learning on a 200 TB dataset, using around 200 machines.

I copied this approach from several papers, with some improvements, for my datastore.

I have a server with hundreds of routes, representing all the possible operations I can do on a datastore. How can I organize my code better?

Yes I'm building a database where storage and compute are decoupled. I use io_uring to do pseudo-RDMA, and I'm looking to add ePBF to make it even more effective.

I'm currently building an implementation of the dynamo paper, yottastore. Imagine it as a huge, distributed, hash map.

I'm building an implementation of the dynamo paper, yottastore. Given a key, I need to find which NVMe block stores the data. To do that I hash the key to find the shard where I have an in memory array in which at position [hash] I can find a struct with:

I have to be honest, I'm very skeptical about your results and your code. I'm building a database, yottastore, both in javascript, golang and rust so I think I can share my opinion:

Based on this [GitHub document](https://github.com/etcd-io/bbolt) for BBoltDB, we can understand that Go Code be used to create a BBoltDB database on the system. The key-values added & operations done on them in that Go Code are stored in the BBoltDB database.

A Locker is a store on your file system (built on top of the amazing bbolt).

- bbolt for storage on disk. In order to get the smallest db file size possible make sure you insert the keys in order and set:

I'm wanting to store some wasm modules (as []byte) in BoltDB. Right now the modules are <1MB, but eventually, they could be 10-50MB in size. Is this going to reduce the performance of BoltDB all around, if the size of a value is this large? If it makes a difference, I'm using the Storm toolkit for querying.

bbolt - An embedded key/value database for Go.

For learning goroutines and channels, I usually recommend writing a program that reads from files and writes the data in a dummy database with something like https://github.com/etcd-io/bbolt. It's relatively simple and you're more likely to run into common manifestations of concurrency issues running disk operations.

If you would like to explore usage of channels, I highly recommend writing a program that reads from files and writes the data in a dummy database with something like https://github.com/etcd-io/bbolt.

No transactions, no consistency guarantees, no benchmarks, global locks in the storage implementation, a collection is copied in its entirety on every insertion to it...I realize it's not for the same use case as MySQL or MongoDB, but a more obvious comparison here is e.g. https://github.com/etcd-io/bbolt. So why should someone use this over bbolt?

use go-sqlite3 to work with sqlite3 is one choice.

https://github.com/etcd-io/bbolt is another pure go option.

cznic seems like an alternative to bbolt. nice to have some options.