NoSQL databases are often categorised under four main types. Some databases are a mix between different types, but in general, they fit under the following main categories.
A column store database is a type of database that stores data using a column oriented model.
A column store database can also be referred to as a:
- Column database
- Column family database
- Column oriented database
- Wide column store database
- Wide column store
- Columnar database
- Columnar store
A document store database (also known as a document-oriented database, aggregate database, or simply document store or document database) is a database that uses a document-oriented model to store data.
Document store databases store each record and its associated data within a single document. Each document contains semi-structured data that can be queried against using various query and analytics tools of the DBMS.
A key-value database (also known as a key-value store and key-value store database) is a type of NoSQL database that uses a simple key/value method to store data.
The key-value part refers to the fact that the database stores data as a collection of key/value pairs. This is a simple method of storing data, and it is known to scale well.
NoSQL is a term that refers loosely to a particular type of database model, or database management system (DBMS).
NoSQL is a very broad term that doesn’t refer to one particular database model. Rather, it refers to a whole variety of different models that don’t fit into the relational model.
Although NoSQL databases have been around since the 1960s, it wasn’t until the early 2000s that the NoSQL approach started to pick up steam, and a whole new generation of NoSQL systems began to hit the market.
In database systems, ACID (Atomicity, Consistency, Isolation, Durability) refers to a standard set of properties that guarantee database transactions are processed reliably.
ACID is especially concerned with how a database recovers from any failure that might occur while processing a transaction.
An ACID-compliant DBMS ensures that the data in the database remains accurate and consistent despite any such failures.
Graph databases have been gaining popularity over recent years as a viable alternative to the relational model. Graph databases are particularly well suited to storing connected data – data with lots of interconnected relationships, especially those that run many levels deep.
This article looks at the main differences between graph databases and relational databases.
A graph database is a database that uses a graphical model to represent and store the data.
The graph database model is an alternative to the relational model.
In a relational database, data is stored in tables using a rigid structure with a predefined schema.
In a graph database, there is no predefined schema as such. Rather, any schema is simply a reflection of the data that has been entered. As more varied data is entered, the schema grows accordingly.
This article is part 2 of the database tutorial.
Here, we cover:
- The different ways of adding data to a database
- Querying a database
This article is part 1 of the database tutorial.
Here, we cover the following:
- What is a database?
- What is a Database Management System (DBMS)?
- Types of databases
- What does a relational database look like?
- Creating a database
- Creating tables
- Data types