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What is a NoSQL database?

What is a NoSQL database?

The NoSQL database management system is one characterized by the use of flexible data structures and the ability to handle massive volumes of structured, unstructured, or semi-structured data. The term NoSQL is an acronym of “NoSQL Database,” “Not-Only SQL,” or “Non-SQL.” A NoSQL database typically implies that it is not tied to a specific structure, can be distributed across multiple systems, and offers flexibility and scalability.

How are NoSQL databases used?

NoSQL databases are especially suitable for these real-time applications.

  • Social Media activity: NoSQL is helpful in handling extensive unstructured data generated from social media platforms (Facebook, X) for posts, likes, and comments.
  • IoT (Internet of Things) applications: It can manage continuous data streams generated from fitness trackers, security cameras, handheld devices, and sensors.
  • Gaming applications: NoSQL can manage dynamic data from real-time online gaming applications.

Content Management: NoSQL databases are well-suited for managing content as they can efficiently store and retrieve a mix of data types including text, images, audio and videos.

The four types of NoSQL databases

Broadly, there are four types of NoSQL databases:

  1. Document Databases: The database stores data in a semi-structured format using JSON (JavaScript Object Orientation). These documents are schemaless, i.e., each document can have a different structure. The JSON documents are well suited for web or real-time data analytics applications. It is an excellent choice for applications whose data structure changes frequently. Examples: Amazon DocumentDB, MongoDB, Couchbase.
  1. Key-value databases: The key-value database consists of key-value pairs. Each unique key is associated with a data value. These databases suit session management, Web application caching, and multiplayer gaming. The key-value databases are optimized for fast read-write operations.

Examples: Amazon DynamoDB, Redis, Aerospike, and Riak.

  1. Graph databases: Graph databases deal with complex relationships. They use graph structures consisting of nodes and edges. Each node is similar to a row in a relational database; edges represent relationships between nodes.. Graph databases represent relationships such as social media connections and customer relationship management.

Examples: Neo4j, Amazon Neptune, OrientDB.

  1. Wide-Column stores: The wide-column databases store data in columns. Each column is stored in a separate file. These databases help handle large amounts of data.

Example: Amazon SimpleDB, Cassandra.

The four types of NoSQL databases

What differences are there between NoSQL vs SQL databases?

Here are some differing characteristics between NoSQL vs SQL database management systems.

  • Data Model (Structure): The SQL relational database stores data using a pre-defined schema in rows and columns. These tables have logical relationships using constraints. All new or existing data must adhere to the table schema. The NoSQL databases are flexible and contain different data models: Key-value, Document, Graph, and Wide-Column stores, as defined earlier.
  • Schema: In the SQL database, you define the table schema (Columns, data types, and their properties) and their logical relationships before starting to work with data. The NoSQL database does not need a fixed structure, and the data format can be flexible, reducing the development complexity.
  • Scalability: The SQL database generally scales vertically, i.e., by increasing computing power (CPU and memory) for handling large workloads or improving performance. NoSQL databases scale horizontally, often automatically, spreading data and workload across any number of servers or clusters - and less costly when using commodity hardware. Some SQL databases provide options to configure for vertical scaling, as well..
  • Properties: SQL databases follow the Atomicity, Consistency, Isolation, Durability (ACID) rule for each transaction. NoSQL databases use different mechanisms for data consistency, and consistency is only possible in varying combinations (pairs) of availability and partition tolerance, depending on the specific NoSQL database. For more detail, refer to Brewer's CAP theorem. For one example, MongoDB is structured to achieve both availability and partition tolerance, but not immediate/constant consistency.
  • Use cases: The SQL relational databases are suitable for Online transaction processing (OLTP) or Online analytical processing (OLAP) applications for high transactional and consistency requirements. The NoSQL databases are useful for handling semi-structured or unstructured data with low-latency applications.

What are the benefits and advantages of NoSQL databases?

NoSQL databases can yield the following benefits and advantages:

  1. Flexibility: The flexible schema allows working with semi-structured or unstructured data without using a pre-defined schema. It makes it suitable to adapt to the changing data requirements.
  2. Performance: The NoSQL databases offer low latency data access and optimized data operations. Therefore, they are ideal for handling real-time applications or high-traffic websites.
  3. Scalability: NoSQL databases can handle a large amount of data and traffic as data is horizontally scalable. You can add or remove data nodes as required without much complexity.
  4. Availability: The NoSQL databases offer features to run the databases without interruption in case of hardware failures or network fluctuations.
  5. Cost-efficiency: NoSQL databases are more cost-effective than traditional relational SQL databases.
  6. Flexible development: NoSQL databases use the popular JavaScript Notation (JSON) documents that are development-friendly and easy to adapt to applications.

Are there any drawbacks of using NoSQL databases?

There are some disadvantages of using NoSQL databases. The common issues are described below.

  1. A lack of standardization: Each NoSQL database brand uses a schema that is unique to that brand. As such, each NoSQL database technology has its own unique strengths and weaknesses.
  2. A lack of ACID compliance: The traditional SQL databases are ACID compliant, which makes them fully reliable and consistent. The NoSQL databases do not guarantee full compliance for ACID properties. Therefore, a NoSQL database is a difficult choice if you need an application with strong data consistency requirements.
  3. A lack of joins: The SQL databases can establish relationships among multiple tables using joins and constraints. With NoSQL databases, it is challenging to handle the complex relationships among data or documents and may require application logic to handle these.
  4. Horizontal scaling cost: NoSQL database supports horizontal scaling. Therefore, you need multiple servers or clusters to scale a NoSQL database, and the price of multiple servers can be high compared to vertical scaling in the relational database. However, when commodity hardware can be used, horizontal scaling can be quite cost-efficient compared with vertical scaling on larger servers.

Where can I get help for NoSQL databases?

Quest provides solutions to help you model, develop, manage, monitor, backup and recover your NoSQL database environments.

See how to monitor NoSQL

See how Foglight Cloud provides performance monitoring of your SQL and NoSQL databases.