choosing-database

Choosing a Database

• Overview
• Important Questions to Ask
• Relational
• Non-Relational

Overview

The reason that we have many database options available today is due to the CAP theorem.

CAP Theorem: At any given time, you can only guarantee two of the following: consistency, availability, and partition tolerance.

Important Questions to Ask

• How many relationships are in your data?
• What is the level of complexity in your data?
• How often do the data change?
• How often does your application query the data?
• How often does your application query the relationship underlying the data?
• How often do your users update the data?
• How often do your users update the logic in the data?
• How critical is your Application in a disaster scenario?

Relational

Examples: SQL Server, MySQL, Oracle database, PostgresSQL, IBM DB2.

Relational databases traditionally feature strong consistency and high availability at the expense of partition tolerance.

• Advantages

  • Optimized for writes
  • Simplicity
  • Ease of data retrieval
  • Data integrity
  • Flexibility

• Disadvantages

  • Costly
  • Structured limits (i.e, field lengths)
  • Isolation

Non-relational

Examples: Memcached, Redis, Coherence, HBase, BigTable, Accumulo, MongoDB, CouchDB.

Non-relational databases have been developed to serve availability and partition tolerance needs mostly. Great for data that's unstructured or not relational at all, or for only serializing/deserializing data (JSON, XML, YAML, etc).

• Advantages

  • Super-low latency
  • Handles massive amount of data
  • Flexibility (store structured, semi-structured, and unstructured data)
  • Agile Programming (ease of evolving on iterations)
  • Inexpensive scalability (efficiently scale out)

• Disadvantages

  • Do not perform ACID transactions
  • Rely on "eventual consistency"
  • Lacks standardization
  • Not all non-relational databases are good at automating the process of sharding, or spreading the database across multiple nodes.