Why choose a NoSQL database? There are many good reasons

NoSQL, short for “Not only SQL”, is a term used for database systems that store information in a variety of formats to meet requirements that traditional relational (or SQL) databases struggle to meet. . Old relational systems were designed to minimize data duplication at a time when storage was extremely expensive.

While relational databases are still widely used, the nature of data storage and use has changed. Things like Google-style search, for example, are built into the majority of apps. The explosion of data, web browsing, mobile usage and analytics have dramatically changed the requirements of modern databases. These new needs have led to the growth of NoSQL databases and include a variety of models such as key value, document, column, time series, and chart. Additionally, leading NoSQL databases now also include key relational features.

What is a Modern Multi-Model NoSQL Database?

Multiple data access methods, also known as multi-models, make databases useful for a wide variety of use cases. JSON (JavaScript Object Notation) is a common NoSQL data format that offers flexibility and works well with different access patterns. NoSQL databases work like a back-end content store, meaning you enter data into a single application, but can access it in multiple ways, depending on the use case. This facilitates the development and evolution of applications over time. Many NoSQL databases are designed from the ground up to be fast, flexible, and highly available, supporting modern cloud computing, distribution, and data management needs.

Why Organizations Choose NoSQL

A key driver is the need to deliver an exceptional customer experience, a key competitive differentiator. Customers expect superb digital experiences with on-demand, real-time, personalized and responsive services. Therefore, applications must be dynamic, work on multiple devices and constantly evolve. Managing this rate of change is not easy without the right technology. This is why many organizations choose NoSQL.

Relational vs NoSQL: main differences

Relational databases were designed for back-office business applications that reside on a server. To expand your database, you needed a larger box, known as “vertical scaling”.

NoSQL databases were born out of the massive growth of data around the internet. Google and Amazon paved the way in the mid-2000s. Efficient, distributed, and highly scalable key-value engines were key to this evolutionary stage. Since then, modern databases have been designed to meet the next generation of scale and flexibility. These databases offer distributed systems that provide high availability by automatically distributing data across multiple nodes as servers are added. With JSON data models and multi-model access, a NoSQL database can meet massive performance demands while scaling rapidly, delivering both new and accelerated customer experiences.

SQL support in NoSQL

Relational systems keep data in a rigid, bound design or table schema. Object data is divided into separate tables to eliminate repetitive information, called normalization. While effective, this is often limited when new features require changes to the data model. NoSQL systems can contain hierarchical JSON data, supporting more structure and needs such as ACID transactions, while also providing flexible semi-structured ways to store and return data. This convergence of the best of relational and the best of modern NoSQL simplifies information architectures and application development and helps support modern database needs such as:

  • Deliver highly responsive experiences across web and mobile.
  • Processing of semi-structured and unstructured data, while supporting the needs of ACID transactions.
  • Adapt quickly to changing user needs with frequent updates.
  • Release new features with faster time to market.
  • Support for multiple data types and data access methods.
  • Ensure high availability without downtime.

These needs could be met with relational databases, but the effort and costs would be very high.

Develop with agility

Speed ​​is essential to innovation, but so is flexibility. A fundamental principle of agile development is to react quickly to change. Often when the requirements change, the data model must also change. With relational databases, developers often have to formally request a “schema change” from database administrators. This slows or stops development.

In comparison, a NoSQL document database fully supports agile development because it is schemaless and does not statically define how the data should be modeled. Instead, it defers to applications and services, and therefore developers, as to how the data should be modeled. With NoSQL, the data model is defined by the application model.

Applications and services model data as objects (such as the employee profile), multivalued data as arrays (roles), and related data as nested objects or arrays ( for example, the manager’s relationship). Relational databases, however, model data as tables of rows and columns – related data as rows in different tables, multi-valued data as rows in the same table. Data is read and written by disassembling and reassembling objects.

In contrast, a document-oriented NoSQL database reads and writes data formatted in JSON, which is the de facto standard for consuming and producing data for web, mobile, and IoT applications. Objects are read and written without disassembling them. NoSQL databases have logical hierarchical groupings, called collections and/or scopes, to organize subsets of documents, which can be limited to particular users, features, or workloads.

Operate at any scale

Databases that support web, mobile, and IoT applications must be able to operate at any scale. Massive scaling of a relational database like Oracle is usually complex, expensive, and not entirely reliable. Distributed NoSQL databases run on commodity hardware and are designed to scale – for example, to add more resources, you can simply add another server (aka “horizontal scaling”). The ability to scale helps teams by not deploying more hardware than necessary to meet the current load; apply less expensive hardware and/or cloud infrastructure; and scale on demand and without downtime. Additionally, advanced replication between data centers extends high availability worldwide.

Query using SQL and ACID transactions in NoSQL

Application developers who are used to querying with SQL can continue to use the same language in NoSQL platforms, but operate on stored JSON data. Some modern cloud database vendors provide an SQL-based query language that returns results in JSON format with rowsets and subdocument components where applicable, supports advanced JOINs, and can be used for analysis. This contrasts with the majority of other NoSQL databases.

Due to the normalization of objects in multiple data tables, relational systems can often require a transaction for almost every update. With NoSQL databases, updates typically involve a single document and do not require a transaction. Some advanced NoSQL databases support distributed multi-document ACID transactions.

Database as a service

Typically, a database as a service (DBaaS) streamlines operations and reduces the amount of work teams have to perform, such as installing and configuring infrastructure as a service, provisioning the database data, operations management, scaling automation, monitoring and security.

From a financial and operational perspective, companies see benefits such as:

  • Quick setup
  • Ability to evolve
  • Quick configuration changes
  • High service levels
  • Security Automation

NoSQL supports modern needs

Tens of thousands of organizations have adopted NoSQL. Choosing the right cloud database platform isn’t easy. To support critical applications, many enterprises choose Couchbase Capella to improve resiliency, performance, and stability, while reducing risk, data sprawl, and total cost of ownership. And developers love Couchbase because it combines the flexibility and agility of NoSQL with familiar relational database concepts. That’s why 30% of Fortune 100 companies manage critical data with the Couchbase database platform.

Try Couchbase for yourself today with our free trial.

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