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4D vs Boost: What are the differences?
Introduction:
When comparing 4D and Boost, it is crucial to understand the key differences between the two technologies to choose the most suitable option.
Database Model: 4D is a relational database management system (RDBMS) that uses tables to store data, while Boost is a multi-model database that supports various data models, including key-value, document, and graph. This difference allows Boost to handle different types of data structures more efficiently compared to 4D.
Scalability: 4D is designed for small to medium-sized databases, limiting its scalability capabilities. In contrast, Boost is scalable both vertically and horizontally, making it well-suited for high-demand applications or expanding data needs. This scalability feature gives Boost an edge over 4D in terms of handling large amounts of data.
Query Language: In 4D, SQL is the primary query language used to interact with the database, offering traditional database querying capabilities. Boost, on the other hand, supports multiple query languages, including SQL, GraphQL, and custom APIs, providing more flexibility in querying and manipulating data. This versatility in query languages gives Boost a wider range of functionalities compared to 4D.
Community Support and Documentation: Boost has a larger community of developers and users, resulting in more extensive documentation, tutorials, and forums for support. In comparison, 4D has a smaller community, leading to limited resources for troubleshooting and learning. The robust community backing and documentation make Boost a more accessible and well-supported option than 4D.
In Summary, understanding the differences between 4D and Boost in terms of database model, scalability, query language, and community support is essential in making an informed decision for choosing the appropriate technology for your project.
