DataBase

1. Standards: ACID Compliance
2. Types (Need Not be Mutually Exclusive)
3. Auxiliary features
4. Sentinels
- 4.1. Entity Relation Diagrams

Towards managing data stores.

Speaking formally, databases represent another layer of abstraction over a computer system's filesystem that intend to provide convenient endpoints for tasks (like templated insertion, deletion, searches, etc) that would be performed with higher frequencies : they facilitate structured storage, pushing for reliability and efficiency.

1. Standards: ACID Compliance

Atomicity
Consistency
Isolation
Durability

checkout : https://docs.digitalocean.com/glossary/acid/

2. Types (Need Not be Mutually Exclusive)

2.1. Relational Databases

2.1.1. Tools

PostGres
- RDBMS
- Open Source with all the bells and whistles
  - the recommended choice
MySQL
- RDBMS
- open source without all the bells and whistles
  - batteries included though
SQLite
- RDBMS : single file
- open source : spartanish
- has its moments : https://www.sqlite.org/whentouse.html

2.1.2. Extensions

Object Relational Mappers
- Coms with the database without sql queries : language specific
  - read up for the case of python
- some issues do arise:
  - Impedence mismatch
  - performance issues
- Personally, I'd rather write raw SQL : see stored procedures
- still, checkout sqlAlchemy

2.2. Graph Databases

three storage aspects
- Node
- Edge
- Property

2.2.1. Tools

Neo4j
Cayley
Titan

2.2.2. Resources

2.3. Document Stores

2.3.1. Tools

semi structured representation for nested data (json,bson,etc)

MongoDB
Riak
Apache CouchDB

2.4. Key-Value Stores

underlying data stucture being the HashMap

2.4.1. Tools

Redis
- in memory
- good for caching, queuing, and storing session data and requests
- check out : https://realpython.com/python-redis/
Memcached

2.5. Columnar Databases

builds on key-value pairs
each pair a row in a store while each column family is similar to a table in the relational model.

2.5.1. Tools

Apache Cassandra
Apache HBase

2.6. In-Memory Databases

2.7. Time-Series Databases

2.8. NewSQL Databases

3. Auxiliary features

3.1. Data Replication

one master, multiple read-only slaves (different than sharding)

3.2. Semi-structured storage opportunities

JSON type in RDBMS for instance

3.3. Sharding

horizontal scaling for multiple read/write instances
- introduces delays for maintenance of data consistency

3.4. Monitoring

Profiling processes, analysing frequency of certain queries, etc, help with better structuring the templates (index, schema, etc) to push for performance