Complexity of Distributed Systems: Managing distributed NoSQL clusters can be complex
Posted: Tue May 20, 2025 7:17 am
Data Integrity Challenges: The lack of strict schema enforcement and ACID properties can sometimes lead to data inconsistencies if not managed carefully at the application level.
Maturity and Tooling: While the NoSQL ecosystem is growing, some models are less mature than RDBMS, and tooling might be less extensive.
Query Language Diversity: Unlike the standardized SQL, NoSQL databases often have their own query languages, which can increase the learning curve.
Limited Support for Complex Transactions: Strict ACID transactions are not always a priority in NoSQL databases.
Typical Use Cases:
Web Applications: , personalization, and real-time data.
Big Data Analytics: Storing and processing massive datasets for analysis and insights.
Real-time Data Processing: Handling high-velocity data streams.
Mobile Applications: Providing flexible and scalable backends for mobile apps.
Internet of Things (IoT): Managing data from a large number netherlands whatsapp mobile phone number list of connected devices.
NewSQL databases emerged as an attempt to combine the scalability and flexibility of NoSQL with the ACID properties and SQL interface of traditional RDBMS. They aim to provide the best of both worlds for applications that require both high scalability and strong consistency.
SQL Interface: NewSQL databases typically support SQL, making migration from RDBMS easier and leveraging existing SQL expertise.
ACID Properties: They strive to maintain full ACID compliance for transactional integrity.
Horizontal Scalability: Architectures are designed for distributed environments, enabling horizontal scaling.
Various Architectures: NewSQL encompasses different architectural approaches, including:
Distributed SQL: Extending traditional SQL databases to run across a distributed cluster.
Shared-Nothing Architectures: Each node in the cluster is independent and manages its own data.
SQL on NoSQL: Providing a SQL interface on top of a NoSQL storage engine.
Maturity and Tooling: While the NoSQL ecosystem is growing, some models are less mature than RDBMS, and tooling might be less extensive.
Query Language Diversity: Unlike the standardized SQL, NoSQL databases often have their own query languages, which can increase the learning curve.
Limited Support for Complex Transactions: Strict ACID transactions are not always a priority in NoSQL databases.
Typical Use Cases:
Web Applications: , personalization, and real-time data.
Big Data Analytics: Storing and processing massive datasets for analysis and insights.
Real-time Data Processing: Handling high-velocity data streams.
Mobile Applications: Providing flexible and scalable backends for mobile apps.
Internet of Things (IoT): Managing data from a large number netherlands whatsapp mobile phone number list of connected devices.
NewSQL databases emerged as an attempt to combine the scalability and flexibility of NoSQL with the ACID properties and SQL interface of traditional RDBMS. They aim to provide the best of both worlds for applications that require both high scalability and strong consistency.
SQL Interface: NewSQL databases typically support SQL, making migration from RDBMS easier and leveraging existing SQL expertise.
ACID Properties: They strive to maintain full ACID compliance for transactional integrity.
Horizontal Scalability: Architectures are designed for distributed environments, enabling horizontal scaling.
Various Architectures: NewSQL encompasses different architectural approaches, including:
Distributed SQL: Extending traditional SQL databases to run across a distributed cluster.
Shared-Nothing Architectures: Each node in the cluster is independent and manages its own data.
SQL on NoSQL: Providing a SQL interface on top of a NoSQL storage engine.