SenseiDB was initially developed and employed by LinkedIn team in 2009. Engineers from both LinkedIn and Xiaomi were working on the project. It then became an open-source project that was contributed by many individuals. After three releases, SenseiDB has no longer updated or used since year 2013.
SenseiDB applies an indexing manager called [Zoie](http://javasoze.github.io/zoie/), which is an independent searching and indexing engine built on [Apache Lucene](https://pdfs.semanticscholar.org/2795/d9d165607b5ad6d8b9718373b82e55f41606.pdf) that uses inverted index to efficiently retrieve data. The biggest feature of Zoie is the support for real-time searches and updates.
N-ary Storage Model (Row/Record)
A SenseiDB instance is a table of data that is organized into columns. The attributes of a table is stored as metadata, and each column may belong to one of the supported types: string, int, long, short, float, double, char, date, text.
The entire database is partitioned into a number of shards. Each shard is replicated across N nodes so that there might be more than one shards in a single node. There is not a master node in the system and each node is independent. Upcoming requests go through a separate load balancer to decide the nodes to request.
http://senseidb.github.io/sensei/
https://github.com/linkedin/sensei
http://senseidb.github.io/sensei/overview.html
LinkedIn, Xiaomi
2012
2013
Open Source
Java, Python
All OS with Java VM