What is NoSQL?
With the quantity of information in the digital world increasing exponentially, non-relational databases (or NoSQL: Not only SQL) are emerging as an alternative solution to traditional relational systems. They offer a high degree of flexibility, and are also well-suited to managing analytics services and big data. What sets them apart is their ability to process unstructured data efficiently, which is a major challenge for traditional databases.
Main features of NoSQL
NoSQL databases are radically different from traditional systems, and offer flexibility and adaptability in storage. Here are some of their key features.
Managing unstructured and semi-structured data:
Unlike standard SQL databases, which store data in rigid tables composed of rows and columns, NoSQL databases can store information without a predefined schema. This makes NoSQL ideal for processing data in the form of documents, graphs, or key-value pairs, offering great flexibility in manipulating and querying data.
Varied database types:
NoSQL encompasses a variety of database systems, each tailored to specific needs. For example, document-oriented databases, such as MongoDB, are optimised to store and retrieve documents using a JSON format. Key-value databases, such as Redis, offer a quick and easy structure for storing information in key-value pairs. Column-oriented databases, such as Cassandra, are designed to efficiently manage large amounts of information across multiple nodes.
Flexibility in queries and analysis:
NoSQL databases offer a high degree of flexibility in formulating queries. They are capable of managing complex and varied requests, adapted to the nature of the data being stored. This flexibility is particularly beneficial for applications that require custom queries or advanced data analytics.
Data Relationships:
Although NoSQL databases are not oriented toward relationshipsas structured as those in SQL models, they still provide effective ways to manage the relationships between data. For example, in a document-oriented database, documents can contain references to other documents, making it easier to create dynamic links between data.
Scalability and performance:
NoSQL databases are designed to offer good scalability and performance capabilities, especially in distributed environments. They enable large amounts of data to be stored and processed across multiple servers, while maintaining fast response times and high availability.
NoSQL databases: why and when to use them
NoSQL databases are particularly effective in several key scenarios.
Processing large amounts of data in real time:
In environments where data processing speed is critical, such as streaming applications or social media, NoSQL databases offer unparalleled performance. Their ability to manage large volumes of data in real time without compromising on speed is a major asset.
Horizontal scalability:
NoSQL databases can expand easily by adding more servers to the cluster. This is especially useful for fast-growing businesses that need to increase processing and data storage capacity without service disruption.
Applications that require high data flexibility:
Projects where the data structure can grow rapidly benefit from the flexibility of NoSQL databases. They can be used to add new types of data without having to completely overhaul the database schema.
Comparison with relational databases
There are significant differences between NoSQL databases and traditional relational databases.
No fixed schema:
Unlike relational databases, where each table is defined by a strict schema of columns and data types, NoSQL databases do not require a fixed schema. This allows for greater flexibility in data storage and management, especially for unstructured or semi-structured data.
Varied data models:
While relational databases use primarily a tabular model, NoSQL databases support a wider variety of data models, including documents, graphs, and key-value pairs. This diversity allows you to choose the model that is best suited to each type of data and each use case.
Data Relationship Management:
In relational databases, data relationships are managed by foreign keys and joins. In NoSQL databases, relationships are often managed in a more flexible way, using references or nested data structures.
How a NoSQL database works
To understand the mechanism of NoSQL databases, be sure to look at the key elements below.
Typical architecture
NoSQL databases, such as Cassandra or MongoDB, are characterised by a distributed architecture, which is key to managing a large volume of data. This architecture distributes data across multiple servers, improving system availability, resilience, and scalability. In most NoSQL databases, data can be stored and managed efficiently, allowing for a fast response even with a large data volume.
NoSQL database types
- Document Template (MongoDB): Document databases, such as MongoDB, store data in a non-tabular form, often in JSON or BSON format. This makes them perfect for storing semi-structured or unstructured data, offering great flexibility in its management. They are particularly useful when data changes over time or does not follow a fixed pattern.
- Column model (Cassandra): Among NoSQL databases, column-oriented systems like Cassandra are designed to store and manage data efficiently, especially for applications that require fast reading and writing of large amounts of data. These databases are ideal for querying large volumes of unstructured data, where the data is not specifically stored as tables.
- Key-value model (Redis): Key-value databases offer a simple yet powerful structure, where each element is stored as a key-value pair. This simplicity makes them extremely fast for certain operations, especially for applications that require quick access to data.
- Graph model: Graph-oriented databases in data warehouses, such as Snowflake, Databricks, BigQuery or ClickHouse, play a crucial role in large-scale data analysis and storage. These systems, designed to efficiently process structured and semi-structured data, stand out for their performance in data reading and analytics. Perfect for organisations processing high volumes of information, these solutions offer scalability and flexibility, complementing graph-oriented databases in a comprehensive data ecosystem.
Comparative analysis of NoSQL and SQL databases
In today’s fast-changing world of databases, comparing NoSQL and SQL systems is key to understanding their respective strengths and determining which one is best suited to your specific needs.
Fundamental Differences
The main distinction between NoSQL and SQL databases lies in their respective approaches to structuring and managing data. NoSQL systems have been designed to store data in a variety of formats, without requiring a fixed schema or rigid tables. This is in contrast to traditional relational databases, where all data is stored as tables with defined relationships.
Advantages and disadvantages of each solution
In order to determine the best choice between NoSQL and SQL, it is important to understand the fundamental distinctions between these database types.
| Performance criteria | NoSQL | SQL |
| Scalability | ✓ | - |
| Schema flexibility | ✓ | - |
| Managing large amounts of data | ✓ | - |
| Complexity of requests | - | ✓ |
| Data integrity | - | ✓ |
| Data Relationships | - | ✓ |
| Speed of requests | ✓ | ✓ |
| ACID Transaction Support | - | ✓ |
| Adaptability to changes in data structures | ✓ | - |
| Optimisation for specific queries | ✓ | ✓ |
| Support for various data models (documents, key-value, etc.) | ✓ | - |
| Ease of data distribution and replication | ✓ | - |
| Ability to manage unstructured data | ✓ | - |
| Maintenance and upgrade costs | ✓ | - |
Advantages of NoSQL databases
Understanding the fundamental distinctions between NoSQL and SQL databases is key to making the right choice for you.
Scalability
NoSQL databases, such as those offered in cloud database solutions, are characterised by their high scalability. This scalability allows you to efficiently handle exponential growths in data. Unlike traditional relational databases, where increasing load can require complex restructuring, NoSQL databases can be extended simply by adding more resources or nodes to the system, making them ideal for fast-growing applications.
Flexibility
Flexibility is a key feature of NoSQL databases. They allow data to be stored without being constrained by a fixed schema, offering great freedom in how you manage and integrate difference types of data. This unique feature of NoSQL databases makes them particularly well-suited to environments where data can be varied and may grow quickly, such as on social media applications or e-commerce platforms.
Performance
In terms of performance, NoSQL databases have been designed to offer high processing speeds, even when faced with large amounts of data. This efficiency is due in part to their architecture optimised for fast read and write operations, as well as their ability to distribute data across multiple servers. Whether it's for applications that require real-time access or for processing massive data, NoSQL databases provide a robust, high-performance solution.
Challenges and limitations of NoSQL databases
The limitations and challenges that come with NoSQL databases need to be taken into account in order to better understand the key issues and considerations in their use.
Security
While NoSQL databases offer many advantages, security remains a major issue. They may be more vulnerable to certain attacks, such as NoSQL injections. It is therefore crucial to implement robust security strategies, such as data encryption, rigorous access management, and continuous monitoring to protect stored data. Each NoSQL database requires a specific approach to security, tailored to its technology and architecture.
Complexity of data management
Managing data in NoSQL databases comes with its own unique challenges, particularly due to its unstructured nature. Unlike relational databases, where data is stored as tables with predefined schemas, NoSQL databases are used to store data without a fixed schema.
While this flexibility is advantageous in terms of scalability and performance, it can make data management more challenging, especially when it comes to consistency, complex queries, and integration with other systems. It is essential for companies to carefully assess whether the benefits of NoSQL databases are suited to their specific needs, and to be prepared to manage the inherent complexity of these technologies.
Examples and use cases of NoSQL
NoSQL databases can be used in a variety of use cases and business contexts.
Industry case studies
NoSQL databases have become the preferred choice for many companies in different industries, due to their ability to effectively manage big data.
For example, in the retail sector, NoSQL databases are used to store and analyse customer data to optimise the user experience and personalise offerings. In healthcare, they allow large amounts of patient data to be managed, helping to improve healthcare and medical research.
Examples of practical implementation
Platforms such as OpenSearch demonstrate the effectiveness of NoSQL databases in practical applications such as searching and data analysis.
This solution, for example, offers a NoSQL database for quickly indexing and searching large amounts of data, providing a powerful solution for companies requiring real-time data processing and analysis. This database technology is particularly well-suited to environments where the data is highly varied and processing speed is critical.
Here are some other examples of companies that use NoSQL.
Alibaba:
The e-commerce giant Alibaba uses Firebase to optimise its mobile applications. This strategic integration allows it to take advantage of advanced Firebase features, such as real-time database management and push notifications. This improves user experience and strengthens operational efficiency, demonstrating Alibaba’s commitment to technological innovation and customer satisfaction in the dynamic e-commerce sector.
Netflix:
To meet its specific data storage needs, including for its videos and recommendations, Netflix turned to Cassandra. This solution gives Netflix the ability to efficiently manage large-scale data, a crucial asset for a leader in video streaming.
X (formerly Twitter):
The world-famous microblogging platform uses Cassandra to store its post data. This solution enables it to efficiently manage the large quantity of data generated by its active users.
IBM:
IBM is a technology pioneer that uses MongoDB for medical data storage. This approach allows them to benefit from flexible, high-performance data management, which is essential in the healthcare sector.
Choosing between NoSQL and SQL: decision criteria
To guide decision-makers towards the most suitable solution for their specific needs, there are key criteria to consider when choosing between NoSQL and SQL databases.
Assessing your project needs
The choice between a NoSQL and SQL database should be guided by a thorough assessment of the project’s needs. This decision depends largely on the nature and structure of the data being managed. For example, if the project involves processing large amounts of unstructured or semi-structured data, a NoSQL database might be more suitable due to its flexibility and ability to scale easily.
However, for projects that require complex transactions and rigorous data integrity, a SQL database would be better suited because of its well-defined structure and advanced query capabilities.
Comparing available solutions
Before making a decision, it’s important to compare the differentSQL and NoSQL database hosting solutions available on the market. This comparison should take in account scalability, performance, security, manageability, and cost. Businesses should also consider the compatibility of these systems with their existing infrastructure and long-term goals.
For example, NoSQL databases are often favoured for applications that require high scalability and flexible data management, while SQL databases are chosen for their robustness and reliability in managing complex transactions.
Conclusion: the future of databases with NoSQL
Adopting managed databases in the cloud at OVHcloud is a strategic step forward for companies looking to optimise the management of their data. Compared to self-managed solutions, our databases in the cloud offer increased scalability, performance, and security, while reducing operational complexity and costs. This approach allows companies to focus on their core business and innovations, while being supported by a reliable and scalable data infrastructure. With OVHcloud you can transform data management into a driver for growth and operational excellence.
OVHcloud and NoSQL
Your managed MongoDB clusters in a sovereign cloud
Speed up your time to market by entrusting us with the administration of your favourite NoSQL databases. Let your teams focus on their core business and developing your services. We take care of the configuration, maintenance, backup, security and monitoring of your MongoDB database management systems.
Managed Databases for Cassandra
Accelerate your business by deploying a managed Cassandra cluster in just a few clicks. This performance-orientated, open-source NoSQL database engine is perfect for processing more resource-intensive tasks, without compromising on availability. We will manage the service — including configuration, maintenance, backup, high availability and updates — and you can focus on developing your application features.