Why Choose a NoSQL Database? There Are Many Great Reasons

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

Although relational databases are still widely used, the way data is stored and used has changed. Things like Google-style search, for example, are built into most applications. The explosion of data, web browsing, mobile usage and analytics have significantly changed the demands on modern databases. These new requirements have fueled the growth of NoSQL databases and include a variety of models such as key-value, document, column, time-series, and chart. In addition, leading NoSQL databases now also include important relational functions.

What is a modern multi-model NoSQL database?

Multiple data access methods, also known as multimodel, make databases useful for a 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 act as the primary content store, which means you enter the data in an application but can access it in different ways depending on your 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 to support modern cloud computing, distribution, and data management needs.

Why companies choose NoSQL

One of the biggest factors is the need to provide an exceptional customer experience, a key competitive differentiator. Customers expect great digital experiences with services that are on-demand, real-time, personalized and responsive. As a result, applications need to be dynamic, work across multiple devices, and constantly evolve. Without the right technology, managing this pace of change is not easy. For this reason, many companies choose NoSQL.

Relational vs. NoSQL: Key Differences

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

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NoSQL databases were born out of the massive data growth around the internet. In the mid-2000s, Google and Amazon were leaders. Efficient, distributed, highly scalable key-value engines were the key to this evolutionary step. Since then, modern databases have evolved to accommodate the next generation of scalability and flexibility. These databases provide distributed systems that provide high availability by automatically spreading data across multiple nodes as servers are added. With JSON data models and multi-model access, a NoSQL database can meet massive performance demands and still evolve rapidly, delivering both new and accelerated customer experiences.

SQL to NoSQL support

Relational systems manage data in a rigid, linked table design or schema. Object data is split into separate tables to eliminate repetitive information, known as normalization. While efficient, this is often limiting when new features require changes to the data model. NoSQL systems can store hierarchical JSON data, support more structure and requirements such as ACID transactions, while 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 requirements such as: e.g.:

  • Delivering responsive experiences across web and mobile devices.
  • Process semi-structured and unstructured data while supporting ACID transaction requests.
  • Quickly adapt to changing user needs with frequent updates.
  • Release of new features with faster time to market.
  • Support for multiple data types and data access methods.
  • Ensuring high availability without downtime.

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

Evolve with agility

Speed ​​is crucial for innovation, but so is flexibility. A core principle of agile development is to react quickly to changes. When the requirements change, the data model often has to change as well. Relational databases often require developers to formally request a “schema change” from database administrators. This slows down or stops development.

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

Applications and services model data as objects (e.g. employee profile), multi-valued data as arrays (roles), and related data as nested objects or arrays (e.g. manager relationship). Relational databases, on the other hand, model data as row and column tables—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, the de facto standard for consuming and producing data for web, mobile, and IoT applications. Objects are read and written without decomposing them. NoSQL databases have logical hierarchical groupings called collections and/or scopes to organize subsets of documents that can be scoped to specific users, roles, or workloads.

Work at any scale

Databases supporting web, mobile and IoT applications must be able to operate at any scale. Massively scaling a relational database like Oracle is typically complex, expensive, and not entirely reliable. Distributed NoSQL databases run on commodity hardware and are designed to scale out. For example, to add more resources, you can simply add another server (aka “scale out”). The ability to scale out helps teams by deploying no more hardware than is needed to handle the current load. Use of less expensive hardware and/or cloud infrastructure; and scale on demand with no downtime. In addition, advanced replication between data centers extends high availability around the world.

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Query with SQL and ACID transactions in NoSQL

Application developers accustomed to querying with SQL can still use the same language in NoSQL platforms but work with the stored JSON data. Select modern cloud database providers offer a SQL-based query language that returns results in JSON with groups of rows and partial document components, where appropriate, supports advanced JOINs and can be used for analysis. This is in contrast to most other NoSQL databases.

Because of the normalization of objects into multiple data tables, relational systems can often require a transaction for almost every update. For NoSQL databases, updates typically involve a single document and do not require a transaction. Some advanced NoSQL databases support distributed ACID transactions across multiple documents.

database as a service

Typically, a database as a service (DBaaS) streamlines operations and reduces the amount of work that teams need to do, such as B. the setup and configuration of Infrastructure-as-a-Service, database provisioning, operations management, scaling automation, monitoring and security.

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

  • Fast setup
  • Ability to scale
  • Fast configuration changes
  • High level of service
  • security automation

NoSQL supports modern requirements

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

Try Couchbase today with our free trial.

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