influxdb和boltDB簡介——MVCC+B+樹，Go寫成，Bolt相似於LMDB，這個被認爲是在現代kye/value存儲中最好的，influxdb後端存儲有LevelDB換成了BoltDB

influxdb

influxdb是最新的一個時間序列數據庫，最新一兩年才產生，但已經擁有極高的人氣。influxdb 是用Go寫的，0.9版本的influxdb對於以前會有很大的改變，後端存儲有LevelDB換成了BoltDB，讀寫的API也是有了很大的變化，也將支持集羣化，continuous query，支持retention policy,讀寫性能也是哇哇的，能夠說是時間序列存儲的完美方案，可是因爲還很年輕，可能還會存在諸多的問題，就像如今正在開發的0.9同樣，發佈一拖再拖，就是因爲還有些技術壁壘沒有攻陷。

對於influxdb我不想多說些什麼，以後打算開一個專題，專門詳細來講一說這個玩意，由於我看國內幾乎沒有詳細的文章來說influxdb的。

若是你想讓你的Go應用中的數據持久化，大多數人會使用一些數據庫。最簡單最方便的選擇是嵌入式數據庫，有不少嵌入式數據庫都是C寫的，然而對於Go開發者來講，更但願使用純粹的Golang的解決方案。

Bolt就是這麼一個純粹的Go語言版的嵌入式key/value的數據庫，並且在Go的應用中很方便地去用做持久化。Bolt相似於LMDB，這個被認爲是在現代kye/value存儲中最好的。可是又不一樣於LevelDB，BoltDB支持徹底可序列化的ACID事務，也不一樣於SQLlite，BoltDB沒有查詢語句，對於用戶而言，更加易用。

BoltDB將數據保存在一個單獨的內存映射的文件裏。它沒有wal、線程壓縮和垃圾回收；它僅僅安全地處理一個文件。

LevelDB和BoltDB的不一樣

LevelDB是Google開發的，也是一個k/v的存儲數據庫，和BoltDB比起起來有很大的不一樣。對於使用者而言，最大的不一樣就是LevelDB沒有事務。在其內部，也有不少的不一樣：LevelDB實現了一個日誌結構化的merge tree。它將有序的key/value存儲在不一樣文件的之中，並經過「層級」把它們分開，而且週期性地將小的文件merge爲更大的文件。這讓其在隨機寫的時候會很快，可是讀的時候卻很慢。這也讓LevelDB的性能不可預知：但數據量很小的時候，它可能性能很好，可是當隨着數據量的增長，性能只會愈來愈糟糕。並且作merge的線程也會在服務器上出現問題。LevelDB是C++寫的，可是也有些Go的實現方式，如syndtr/goleveldb、leveldb-go。

BoltDB使用一個單獨的內存映射的文件，實現一個寫入時拷貝的B+樹，這能讓讀取更快。並且，BoltDB的載入時間很快，特別是在從crash恢復的時候，由於它不須要去經過讀log（其實它壓根也沒有）去找到上次成功的事務，它僅僅從兩個B+樹的根節點讀取ID。

按照官方說法，boltDB特色：

Comparison with other databases

Postgres, MySQL, & other relational databases

Relational databases structure data into rows and are only accessible through the use of SQL. This approach provides flexibility in how you store and query your data but also incurs overhead in parsing and planning SQL statements. Bolt accesses all data by a byte slice key. This makes Bolt fast to read and write data by key but provides no built-in support for joining values together.

Most relational databases (with the exception of SQLite) are standalone servers that run separately from your application. This gives your systems flexibility to connect multiple application servers to a single database server but also adds overhead in serializing and transporting data over the network. Bolt runs as a library included in your application so all data access has to go through your application's process. This brings data closer to your application but limits multi-process access to the data.

LevelDB, RocksDB

LevelDB and its derivatives (RocksDB, HyperLevelDB) are similar to Bolt in that they are libraries bundled into the application, however, their underlying structure is a log-structured merge-tree (LSM tree). An LSM tree optimizes random writes by using a write ahead log and multi-tiered, sorted files called SSTables. Bolt uses a B+tree internally and only a single file. Both approaches have trade-offs.

If you require a high random write throughput (>10,000 w/sec) or you need to use spinning disks then LevelDB could be a good choice. If your application is read-heavy or does a lot of range scans then Bolt could be a good choice.

One other important consideration is that LevelDB does not have transactions. It supports batch writing of key/values pairs and it supports read snapshots but it will not give you the ability to do a compare-and-swap operation safely. Bolt supports fully serializable ACID transactions.

LMDB

Bolt was originally a port of LMDB so it is architecturally similar. Both use a B+tree, have ACID semantics with fully serializable transactions, and support lock-free MVCC using a single writer and multiple readers.

The two projects have somewhat diverged. LMDB heavily focuses on raw performance while Bolt has focused on simplicity and ease of use. For example, LMDB allows several unsafe actions such as direct writes for the sake of performance. Bolt opts to disallow actions which can leave the database in a corrupted state. The only exception to this in Bolt is DB.NoSync.

There are also a few differences in API. LMDB requires a maximum mmap size when opening an mdb_env whereas Bolt will handle incremental mmap resizing automatically. LMDB overloads the getter and setter functions with multiple flags whereas Bolt splits these specialized cases into their own functions.

 

參考：

http://www.opscoder.info/boltdb_intro.html

https://github.com/boltdb/bolt