Sistem Basis Data NoSQL

(R)akademi
11 Oct 202104:31

Summary

TLDRThis video discusses the concepts of SQL vs NoSQL databases, focusing on distributed systems and the challenges of scaling. It introduces NoSQL as a solution for modern data types and large-scale applications, highlighting its open-source, distributed, and non-directional nature. The video covers the importance of systems like MongoDB and Redis for handling large datasets and dynamic structures. Additionally, it explores key database principles like consistency, availability, and partitioning, advising on the choice between SQL and NoSQL based on application needs, such as banking systems requiring high consistency or applications benefitting from horizontal scaling.

Takeaways

  • πŸ˜€ Nose call is not a standardized term in database systems, but it refers to a type of non-SQL database system that is open-source, distributed, and non-directional.
  • πŸ˜€ 'NutrIGold' is an example of a Nose call system with features like being open-source, distributed, and non-directional.
  • πŸ˜€ A database system like Oxygold uses a 'Kian value', such as user ID and highest score, as part of its credit system.
  • πŸ˜€ Distributed databases can store data across multiple servers, forming large clusters to improve scalability and fault tolerance.
  • πŸ˜€ NoSQL databases are useful when SQL databases can't meet the needs of modern applications, especially when handling complex or rapidly changing data.
  • πŸ˜€ Migrating data to a new SQL schema can be time-consuming and inefficient, especially when large amounts of data are involved, making NoSQL solutions more practical in certain scenarios.
  • πŸ˜€ NoSQL databases support 'horizontal scaling', allowing additional servers to be added to clusters to handle larger data volumes, unlike SQL databases which typically require 'vertical scaling'.
  • πŸ˜€ Horizontal scaling in NoSQL systems is cost-effective and efficient, particularly as the demand for computational power and storage grows.
  • πŸ˜€ Different types of NoSQL databases include 'key-value stores' like Redis and RocksDB, and 'column-family stores' like Google Bigtable and Cassandra.
  • πŸ˜€ The CAP Theorem explains that a database can only prioritize two out of three properties: Consistency, Availability, and Partition tolerance. The choice depends on the specific needs of the application, such as handling sensitive data or prioritizing speed.

Q & A

  • What is NoSQL and how does it differ from SQL?

    -NoSQL is a type of database that is not based on SQL. Unlike SQL databases, which are structured around tables and schemas, NoSQL databases are designed to handle unstructured data and can be more flexible in terms of the data models they support. They can also scale horizontally, which makes them ideal for handling large volumes of distributed data.

  • What is the significance of the term 'Nose call' in database systems?

    -The term 'Nose call' does not have a standardized definition but is used informally to refer to non-SQL systems. It highlights the shift from traditional SQL databases to more flexible NoSQL databases, which are not bound by strict schemas and can handle various types of data.

  • What are the key characteristics of NoSQL systems?

    -Key characteristics of NoSQL systems include being open-source, distributed, and non-directional. These features allow NoSQL databases to handle large-scale data across multiple servers and provide flexibility in terms of data storage and retrieval.

  • Why are NoSQL databases important for handling new types of data?

    -NoSQL databases are important because they can handle new data types that traditional SQL databases may not support. For example, data from Internet of Things (IoT) systems often has a different structure that doesn't fit neatly into SQL's rigid schema. NoSQL systems can adapt more easily to these changes.

  • What are the challenges of working with SQL databases when schema changes are required?

    -In SQL databases, changing the schema can be challenging because it often requires migrating data from old tables to new ones. This process can be slow and complicated, especially if the dataset is large, making it difficult to implement schema changes in real-time.

  • What is horizontal scaling and why is it beneficial for NoSQL databases?

    -Horizontal scaling involves adding more servers to a system to handle increased load, as opposed to vertical scaling, which involves upgrading individual server components like RAM or CPU. NoSQL databases are designed for horizontal scaling, allowing them to efficiently manage large amounts of data across distributed systems.

  • What is the CAP theorem and how does it apply to NoSQL databases?

    -The CAP theorem states that a distributed database system can guarantee only two of the following three properties: Consistency, Availability, and Partition Tolerance. NoSQL databases often prioritize availability and partition tolerance over consistency, especially when dealing with large, distributed datasets.

  • When should consistency be prioritized over availability in a database system?

    -Consistency should be prioritized in systems where data integrity is critical, such as in banking or financial systems. In these cases, it is essential to ensure that every read operation returns the most recent write, even if it means sacrificing availability temporarily during network failures.

  • What types of NoSQL databases are commonly used, and what are their specific use cases?

    -Common types of NoSQL databases include value stores (like Redis and RocksDB), column-family stores (like Google Bigtable and Cassandra), and graph databases (like Neo4j). Value stores are used for fast key-value retrieval, column-family stores are suitable for large-scale analytics, and graph databases are used for managing relationships in complex data.

  • Why might a developer choose to use MongoDB over a SQL database?

    -A developer might choose MongoDB over SQL if they need a flexible, schema-less database that can easily scale horizontally and handle a variety of unstructured data types. MongoDB is also easier to set up for distributed systems and provides better performance for certain types of applications, such as web and mobile apps.

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Related Tags
NoSQL vs SQLDatabase SystemsScalabilityData ConsistencyHorizontal ScalingCAP TheoremTech TutorialsData ManagementModern DatabasesDistributed SystemsDatabase Types