ScyllaDB data modeling

As the multisource business semantic help of SAP Business Technology Platform, the SAP Data Warehouse Cloud arrangement gives information demonstrating, network, virtualization, and access across the endeavor. Utilizing oversaw spaces, business clients can investigate information, incorporate new data, and offer bits of knowledge.

Conceptual Data Model

A calculated information model recognizes the elements that depict the information and the connections between them. Calculated information models just show the most significant level connections between elements, not properties or essential keys inside the information model.

Physical Data Model

An actual information model distinguishes the table designs that will be underlying the data set, including all tables, segments, essential keys, and unfamiliar keys used to recognize the connections between tables. A social information model is a reason for SQL data sets. Social information models have a proper blueprint and manage organized information. In a social data set administration framework, or RDBMS, the data set is the furthest compartment that has information related to an application.

Data Modelling Techniques

  • Start with the data modelling basics: ask business teams what results they need from the data, and organize the data model around those requirements
  • Build a draft data model with entities and relations, and test the model with best-case and worst-case scenarios
  • Take database queries into account: you should know what your data looks like and what it contains, but also how you intend to query it
  • Assess hardware requirements since servers working with huge datasets can soon run into problems of computer memory and input-output speed.
  • Validate the data model: verify each action (such as your choice of primary key) before moving on to the next step

Why Is Scylla So Performant?

Firstly, Scylla is written in C++. We all know how performant C++ can be if written correctly. On the contrary, Cassandra is written in Java which relies on JVM. With the added garbage collection overhead, Cassandra’s performance gets hurt. In C++, memory management is offloaded to the programmers. This is a win when programmers writing the code are well aware of what they are doing.

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