The profound and ongoing rise of NoSQL cloud databases such as Amazon DynamoDB, MongoDB, and Apache Cassandra signals a significant change in the way organizations manage large and diverse data sets. There is nothing wrong with traditional relational database management systems. In fact, many NoSQL databases have added support for SQL-style queries.
But in a world where enterprises are flooded with unstructured data from mobile, social, cloud, sensors and other sources, NoSQL is clearly better. Compared with RDBMS, it is better at managing large amounts of unstructured data, horizontal flexibility, and schema flexibility.
That is, NoSQL databases are more flexible in the organization of data and easier to use when working with unstructured data. Therefore, choosing between a relational database and a NoSQL cloud database will depend on your needs in terms of architectural structure (data type), data organization, scaling needs, and other factors we examine below.
Relational Databases vs. NoSQL Databases: Comparison Table
| Database type | Schema structure | Zoom method | data organization | Transaction attributes | Easy to use (unstructured data) |
|---|---|---|---|---|---|
| Relational | Predefined | vertical | structured | Comply with acidic | ease |
| NoSQL | Modeless | horizontal | flexible | Meet base standards | simple |
NoSQL database
NoSQL databases are designed for high operating speed and flexibility in the type of data stored and its structure. They are mainly used for large distributed data sets and are particularly effective when processing big data and real-time applications.
See: Non-relational databases find an audience in the growing database market.
Unlike relational databases, NoSQL databases are purpose-built to handle rapidly changing, unstructured data, making them ideal for organizations that deal with dynamic and diverse data formats.
advantage
- Scalability: The horizontal scalability of NoSQL databases makes them ideal for processing large amounts of data.
- Data modeling flexibility: Since NoSQL databases are schema-less, they are well suited for various types of data formats, such as file storage, key-value storage, graph databases, etc.
- High availability: NoSQL databases are designed for distributed environments and provide powerful solutions to maintain high availability, which is critical for continuous operations.
- Easy to use: NoSQL databases are more user-friendly when it comes to managing unstructured data that does not fall into the strict structure of relational databases.
- Performance of unstructured data: NoSQL databases are very good at managing unstructured and semi-structured data, providing high performance in different scenarios.
- Cost effective when scaling: NoSQL databases tend to be more cost-effective than traditional relational databases, especially in cloud environments.
shortcoming
- Learning curve due to lack of standardization: Unlike relational databases that use unified SQL, NoSQL databases have a unique and unique query language that database professionals need to learn and understand.
- Complexity of data consistency: Due to the decentralized nature and eventual consistency model of NoSQL, achieving data consistency is often more complex.
- Limited transaction support: NoSQL databases typically do not provide full atomicity, consistency, isolation, and durability transaction support, which can be a limitation for some applications.
- Backup and recovery challenges: The distributed architecture of NoSQL databases can complicate the backup and recovery process, requiring more complex strategies than RDBMS.
relational database
Relational databases have been around for a long time. Unlike NoSQL databases, they store and provide access to data points that are related to each other. RDBMS is built on a model that expresses dependencies between data using a tabular structure linked by defined relationships.
Advanced: Finding the right database administrator is key to building an effective database.
Relational databases are primarily used for data storage and retrieval operations in applications where data accuracy, consistency, and completeness are critical. They are the backbone of various business applications.
advantage
- Strong consistency: Relational databases are known for their strong consistency model. They are reliable and have predictable data transactions—a key requirement for many business applications.
- Structured data integrity: Relational databases excel at maintaining the integrity of structured data, with well-defined schemas that enforce data types and relationships.
- Mature and standardized: RDBMS technology is mature and has established standards, especially SQL.
- Powerful transaction support: Relational databases provide strong support for ACID transactions, which is critical for applications that require a high level of data accuracy and reliability.
- Advanced security features: RDBMS often have advanced security features and access controls.
- Comprehensive tools and support: Because relational databases have been in the market for a long time, they have a wide range of tools, extensive documentation, and strong community and vendor support.
shortcoming
- Scalability challenges: Scaling a relational database often requires vertical scaling—adding more powerful hardware—which is expensive and has its limitations.
- Rigid architectural design: The predefined schema of an RDBMS makes it less flexible in adapting to changes in data structure. A huge effort is required to modify the existing model.
- Performance issues with large data volumes: RDBMS can face performance bottlenecks when processing large amounts of data or high-speed data, such as in big data applications.
- Dealing with the Complexity of Unstructured Data: Relational databases are not inherently designed to handle unstructured or semi-structured data.
- Cost and resource intensive: Maintaining and extending an RDBMS can be resource-intensive and costly, especially for large databases that require high-performance hardware.
Choose between relational and NoSQL cloud databases
With its strong consistency, structured data integrity, and transaction support, relational databases are ideal for situations where data integrity and order are critical. They prove useful in scenarios that require complex queries and precise data management. However, they face scalability challenges and are less flexible when data continues to change rapidly.
In contrast, NoSQL databases offer unparalleled scalability and flexibility in data modeling. NoSQL databases are also better at handling unstructured data, making them suitable for applications that need to quickly develop and process large amounts of different data types.
However, before deciding to move to NoSQL, you should be aware that while NoSQL databases excel at scalability and flexibility, NoSQL databases typically have a steeper learning curve due to a lack of standardization and may have problems ensuring consistent data Sexual and transactional support poses challenges.
Top relational and NoSQL cloud databases worth considering
No two relational databases or NoSQL cloud databases are the same. They are all unique and best suited for specific use cases. Here are some libraries for your organization to consider.
NoSQL database
- Amazon dynamic database Best suited for organizations or projects that require a highly reliable and scalable NoSQL database with minimal maintenance requirements. It is commonly deployed in web applications, games, mobile applications, IoT, and many other applications.
- MongoDB Atlas It is a fully managed cloud NoSQL service. It is best suited for applications that require a flexible model to support diverse and rapidly changing data formats, especially in web and mobile applications and the Internet of Things.
- Apache Cassandra If you have a scenario that requires high flexibility and fault tolerance, this is a good choice. It has been successfully deployed in multiple data centers and real-time big data applications.
- sofa base If you deal with interactive applications that require high throughput and low latency, such as mobile and edge computing, then this is your NoSQL database of choice.
relational database
- Oracle Cloud Ideal for large enterprise applications that require strong performance, security, and reliability.
- Microsoft SQL Server It’s ideal for organizations looking for a comprehensive relational database solution with strong integration with Microsoft products and services.
- PostgreSQL Ideal for organizations looking for an open source RDBMS and placing a high priority on standards compliance and scalability.
