NoSQL Databases : A Clear and Simple Introduction
Published by
May 23, 2025 01:49 PM
Basic introductory article on NoSQL databases. Key concepts, information structure, models and characteristics.
What is a database?
A database is an organized and structured collection of information that is stored electronically in a computer system. Databases allow data to be stored, retrieved, manipulated, and managed in an efficient manner.
In turn, we must also mention that in the world of technology and data management, there are multiple databases designed to meet different needs and specific use cases. Each type of database is designed to optimize data storage, retrieval, and manipulation based on the particular requirements of an application or environment.
Finally, databases in general can be classified into two large categories, which are:
- Relational databases.
- Non-relational databases.
The second one being the focus of this article. 🤓
Non-relational databases
A non-relational database, also known as a NoSQL (Not only SQL) database, is a type of database that differs from the traditional relational model in terms of its structure and organization. Non-relational databases have the ability to handle large volumes of data and scale horizontally, managing rapid and efficient growth.
Furthermore, NoSQL databases are flexible systems in terms of data schema, allowing changes and updates without requiring extensive modifications to the existing structure.
Information management structure
While in relational databases data is organized in interrelated tables, in NoSQL databases different models or structures are used to store and retrieve information.
Among the most popular models we find:
- Document-based model : In this model, data is stored in documents, which can be similar to JSON or XML. Each document contains structured or semi-structured information, and is organized into collections or folders. Examples of NoSQL databases based on this model are MongoDB and CouchDB.
- Key-value model : In this model, data is stored in key-value pairs. Each value is accessed using a unique key. This model is simple yet efficient in retrieving individual data. Examples of NoSQL databases based on this model are Redis and Amazon DynamoDB.
- Wide-column model : Also known as column-family storage, this model stores data in columns rather than rows. It allows for high scalability and flexibility in querying data. Examples of NoSQL databases based on this model are Apache Cassandra and Apache HBase.
- Graph-based model : In this model, data is represented as nodes (entities) and relationships (connections) between them. This model is ideal for representing and querying complex relationships. Examples of NoSQL databases based on this model are Neo4j and Amazon Neptune.
NOTE 🤓: Each model has its own set of features and benefits, and choosing the right model depends on the specific application requirements and the nature of the data to be stored.
Main features of NoSQL databases
- Flexible data model : NoSQL databases allow for a flexible data model, meaning they do not require a fixed, predefined schema. They can store data dynamically without having to follow a rigid table and column structure. This allows for easy adaptation to changing data requirements and greater agility in application development.
- Horizontal Scalability : NoSQL databases are designed to be horizontally scalable. This means they can handle large volumes of data and increase their capacity by adding more servers to the cluster. Horizontal scalability enables efficient performance and the ability to handle massive workloads by distributing the data across multiple nodes.
- High Availability and Fault Tolerance : NoSQL databases are designed to be highly available and fault tolerant. They use techniques such as data replication and clustering to ensure that data is available even in the event of server or network failures. This ensures that applications can continue to run uninterrupted even in failure situations.
- Optimization for specific use cases : NoSQL databases have been developed to address specific use cases. There are different types of NoSQL databases such as document databases, graph databases, key-value databases, and wide column databases. Each type of NoSQL database is optimized to efficiently handle a particular set of data and types of queries.
- Storing and processing unstructured data : NoSQL databases are well suited for storing and processing unstructured data. They can handle data such as JSON documents, geospatial data, time series data, graph data, and more. This provides flexibility to handle a wide range of data types that do not fit well into the tabular structure of relational databases.
- Higher write scalability : NoSQL databases often offer high write throughput, meaning they can handle large volumes of write operations efficiently. This makes them suitable for applications that generate a lot of write-intensive data, such as social media, event logs, tracking systems, etc.
NOTE 🤓: It is important to note that exact features may vary between different NoSQL databases, as each has its own implementation and specific approach.
NoSQL and Clusters
As mentioned above, one of the main characteristics of NoSQL databases is scalability and data replication, which is why clusters play a key role in this area.
What is a cluster in the context of NoSQL?
In a NoSQL database, a cluster is a group of servers or nodes that work together to store and process data. Instead of having a single database instance on a server, a cluster consists of multiple nodes that communicate and collaborate to provide distributed database functionality.
In a NoSQL cluster, nodes can be physical or virtual and are usually networked. Each node in the cluster has independent storage and processing capacity, allowing workload distribution across nodes and improving database performance and scalability.
⚠️ Considerations on clusters
In some cases, clusters may have outdated information due to the distributed nature and propagation times of changes.
This is because in clusters, data is replicated between nodes, and there may be a period of time during which changes made on one node have not yet propagated to all other nodes in the cluster.
There are different levels of consistency in database clusters, and the choice of consistency level affects the possibility of outdated information. Some NoSQL systems offer strong consistency models, where all nodes in the cluster are guaranteed to have up-to-date data before committing an operation. Other NoSQL systems may offer eventual consistency models, where changes are propagated asynchronously and there may be a time gap during which nodes may have outdated data.
NOTE 🤓: However, it is possible to implement additional mechanisms to minimize the likelihood of outdated information in clusters, such as configuring more frequent replication and synchronization policies or using data reconciliation techniques. These techniques can help reduce the time window in which outdated information can exist in the cluster.
Do NoSQL databases allow relationships?
In general, NoSQL databases are not designed to handle relationships between data in the same way that relational databases are. The main focus of NoSQL databases is to provide horizontal scalability, a flexible data model, and high availability. Therefore, most NoSQL databases do not support relationships, which is also not their strong suit.
However, some NoSQL databases offer functionality that allows for some degree of relationships between data, for example:
- Document databases : Some document databases allow you to include references or links between documents, which can help establish relationships. You can store a reference to a related document within another document, providing a way to access related data. However, managing these relationships must be done manually.
- Graph databases : Graph databases are specifically designed to model and manage relationships. They use nodes to represent entities and edges to represent the relationships between nodes. These databases allow efficient querying and navigation based on the relationships defined in the graph.
- Key-value databases : Key-value databases are not specifically designed to manage relationships, but techniques such as key concatenation can be used to establish implicit relationships between data. This involves combining the keys of different items to indicate a relationship.
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