What is NoSQL? NoSQL Databases Explained

A NoSQL (often interpreted as “Not Only SQL”) database provides a mechanism for storing and retrieving data that is modeled in ways other than the traditional tabular structure of relational databases. Main reasons for embracing NoSQL include simplicity of design, horizontal scaling, and better control of availability.

Table of Content

• What is NoSQL?
• Examples of NoSQL Database
  • Document Database
  • Key-Value Database
  • Wide-Column Store
  • Graph Database
• Features of NoSQL
• Types of NoSQL Databases
  • Key-Value Pair Based
  • Column-Based
  • Document-Oriented
  • Graph-Based
• Advantages of NoSQL
• Disadvantages of NoSQL
• Understanding CAP Theorem
• NoSQL vs SQL

What is NoSQL?

NoSQL databases are homegrown solutions developed to solve the challenges of  large-scale companies like Amazon Dynamo and Google have in place. Some of these challenges included:

• High transaction volumes
• Low-latency access to enormous data sets
• Near perfect service availability in unreliable environments.

These issues were not addressed satisfactorily with the traditional SQL-based solutions even when de-normalizing database schemas, query caching, and data partitioning were considered. This resulted in NoSQL databases being an efficient alternative.

Examples of NoSQL Database

Let’s take a look at some examples of how NoSQL databases are used in practice.

1. Document Database

Description: The data is stored in a document data model using JSON or XML objects.

Features: Each document has fields and values, which may be strings, numbers, nested data, arrays, or Booleans.

Use Case: Developers like this because JSON documents align with programming objects.

2. Key-value Database

Description: Data stored in unique key-value pairs.

Features: Simple schema, High performance for non-complex queries.

Use case: It improves performance and caches results for a fixed period.

3. Wide-column Store

Description: There is a modified table mode that uses key rows by dynamic columns.

Features: Include high flexibility; the row can have different columns from other rows.

Use cases: Storing billions of rows while having millions of columns.

4. Graph Database

Description: Entities that are stored as nodes that include relationships as edges in a case graph database.

Features: Highly fast traversal of data and relationships.

Use Case: Suitable for e-commerce recommendations, social networks, and real-time analytics.

Features of NoSQL

Following are the NoSQL Features:

1. Non-relational

• Does not adopt the relational model.
• No complex features such as query languages and ACID properties.

2. Schema-free

• NoSQL databases may be schema-free or their schemas are relaxed.
• Can support heterogeneous data structures on the same domain.

3. Simple API

• Storage and query interfaces are easy to use.
• It usually uses HTTP REST with JSON for communication

4. Distributed

• Does support distributed execution with auto-scaling and failover abilities.
• Guarantees eventual consistency and uses replication for fault tolerance.

Types of NoSQL Databases

There are primarily four types of NoSQL databases and each category has its unique attributes and limitations. Users can choose the database as per their product requirements.

1. Key-Value Pair Based

Structure: Stores information as key-value pairs.

Use Case: Appropriate for taking care of huge information loads with adaptable information types like strings, JSON, and BLOB.

2. Column-based

Structure: Information is put away column-wise, based on Google’s BigTable paper.

Use Case: Used in information warehouses, business knowledge, and CRM frameworks.

3. Document-Oriented:

Structure: Stores and recovers information as JSON or XML documents.

Use Case: Ideal for CMS, online business, and writing for blog stages.

4. Graph-Based

Structure: Addresses elements as nodes and their relationships as edges.

Use Case: Often used for strategies, informal communities, and spatial information.

Advantages of NoSQL

• Handles big data effictively.
• Flexible schema design that allows changes without downtime.
• Scalability in horizontal scale, thus improving performance.
• Ease in replication for distributed operations
• No need for a different layer of caching.
• Much simpler implementation than RDBMS
• Perfect for modern web-based applications that require high speed.

Disadvantages of NoSQL

• Lack of standardization.
• Fewer query capabilities than that of SQL.
• Lack of efficient handling of relational data.
• The steep learning curve by new developers.
• Consistency problems in distributed systems.
• The maturity of tools and support lags behind traditional RDBMS

Understanding CAP Theorem

The CAP theorem explains the trade-offs in distributed systems:

• Consistency: All nodes have the same data simultaneously.
• Availability: Each request gets an answer.
• Partition Tolerance: The system keeps working even when network partitions occur.

It indicates, according to the theorem, that a distributed system cannot have all three at once. Specific requirements make some trade-offs essential.

The theorem states that you cannot simultaneously have all three; you must make tradeoffs among them. The CAP theorem is sometimes incorrectly described as a simple design-time decision—“pick any two [when designing a distributed sys­tem]”—when in fact the theorem allows for systems to make tradeoffs at run-time to accommodate different requirements.

NoSQL vs SQL

NoSQL can fit into your systems to empower you to handle big data and modern application needs. It offers unmatched flexibility and scalability, so choose the right NoSQL database that actually fits the requirements of the project you are working on.