What is NoSQL?

What Makes NoSQL Different From SQL?

The term “NoSQL,” or “non-SQL,” refers to database management systems that employ a non-relational data model, in contrast to the traditional Structured Query Language (SQL). These systems offer greater flexibility compared to relational databases. NoSQL databases are utilized for tasks such as speeding up website caching (e.g., Redis) or supporting rapid iterative development practices (e.g., MongoDB).

SQL, on the other hand, was designed to manage relational database management systems and is often referred to simply as “SQL databases.” Examples include Microsoft SQL Server and MySQL, which manage structured data with relations among entities and variables. NoSQL systems employ alternative methods for data management, emphasizing flexibility over strict relational structures. The term “NoSQL” can also imply “Not only SQL,” indicating that some NoSQL systems may incorporate SQL-like languages or complement traditional SQL databases.

Staying updated on all NoSQL databases can be challenging. This article provides an overview of the basics and highlights some of the most popular NoSQL databases and database types available. For a comprehensive list, visit the List of NoSQL Database Management Systems on Hosting Data’s website.

What are the Types of NoSQL Databases?

There are numerous types of NoSQL systems, but when people discuss “NoSQL,” they generally refer to four main types: Columnar, Document-oriented, Graph, and Key-value. Some databases, like those from Amazon and IBM, are cloud-based and require operating within their respective ecosystems. Others, such as Redis and MongoDB, can be installed on platforms like Utho or other systems, offering flexibility in deployment and usage according to your needs.

Columnar Databases

Columnar databases, also known as wide-column stores, store data in columns, each in its own file or region within the system storage. At first glance, they resemble traditional relational SQL databases. However, they differ significantly by not having predefined keys, column names, or schemas, which allows for high flexibility. Notable examples include Apache Cassandra and Apache Hadoop.

Document-oriented Databases

Document-oriented databases, also known as document stores, store data as documents, utilizing them in a key-value manner. Each document is identified by a key, which serves as a unique identifier, and the content of the document constitutes the value. These systems cater to users requiring rapid development and robust scalability, particularly suitable for agile projects that emphasize continuous integration and deployment. Notable examples include Couchbase, IBM Cloudant, and MongoDB.

Graph Databases

Graph databases utilize graph structures for semantic queries on highly interconnected datasets, storing data through nodes, edges, and properties. This approach enables direct linking of data, making it ideal for scenarios where relationships between data points are crucial. Graph databases are particularly useful in environments where multiple data stores and applications need seamless interaction. Notable examples include Neo4j and RedisGraph.

Key-value Databases

Key-value databases, also known as key-value stores or tuple stores, utilize associative arrays such as dictionaries or hash tables, where each key is a unique identifier mapped to its corresponding value. Values can range from simple integers or strings to more complex JSON structures and other objects. These databases are ideal for handling large datasets that require scalable, distributed computing and high availability. Notable examples include Redis and RocksDB.

Is Blockchain a NoSQL Database?

While blockchain differs from both SQL and NoSQL databases, it’s not categorized as a NoSQL database either. Blockchain operates as a distributed database that enables non-trusting parties to access a verifiable record of truth, whereas SQL and NoSQL databases are typically administered by single entities. Although NoSQL databases can be used alongside blockchain, as discussed in examples like Couchbase’s synergy with blockchain, blockchain itself is distinct from traditional database models.

Other Types of NoSQL Databases

There are numerous examples of specialized NoSQL databases tailored for specific purposes:

• For ACID transactions in distributed databases: FoundationDB
• For storing and analyzing high-frequency time-series data: Axibase
• For solving basic data science problems for users without statistical backgrounds: BayesDB
• There’s likely a database system that meets your specific needs.