Cloud Storage: Key-value Stores/NoSQL - Distributed and Cloud Systems Micro Specialization
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Cloud Storage: Key-value Stores/NoSQL

Cloud Storage: Key-value Stores/NoSQL

Key-Value Stores provide a flexible, schema-less architecture designed for high scalability and availability, essential for cloud applications. Apache Cassandra and HBase serve as two prominent examples of Key-Value Stores, each with distinctive architectures and operational approaches to data management. The distinction between the eventual consistency of Cassandra and the strong consistency of HBase highlights different strategies in handling distributed data in cloud environments.

27 sections

Sections

Navigate through the learning materials and practice exercises.

  1. 1
    Design Of Key-Value Stores: Fundamentals And Apache Cassandra

    This section covers the design principles of Key-Value stores within NoSQL...

  2. 1.1
    Key-Value Abstraction

    Key-Value Stores provide a flexible and scalable alternative to traditional...

  3. 1.2
    Key-Value/nosql Data Model

    This section explores the characteristics of Key-Value stores as part of...

  4. 1.3
    Design Of Apache Cassandra: A Distributed Column-Family Store

    This section discusses the design principles and characteristics of Apache...

  5. 1.4
    Data Model (Cassandra Specifics)

    This section outlines the data model specifics of Apache Cassandra within...

  6. 1.5
    Data Placement Strategies

    This section covers data placement strategies in Key-Value Stores with a...

  7. 1.6

    This section covers the concept of 'snitches' in Apache Cassandra,...

  8. 1.7
    Writes In Cassandra

    This section discusses the write process in Cassandra, highlighting its...

  9. 1.8
    Bloom Filter

    The Bloom filter is a probabilistic data structure that efficiently...

  10. 1.9

    Compaction in Cassandra is a process that consolidates multiple SSTables...

  11. 1.10

    This section covers key aspects of deletes in databases, especially focusing...

  12. 1.11
    Reads In Cassandra

    This section focuses on the reading processes and mechanisms of Apache...

  13. 1.12

    The Membership section explains how Cassandra manages cluster membership and...

  14. 1.13

    The CAP theorem states that in distributed systems, it's impossible for a...

  15. 1.14
    Eventual Consistency

    Eventual consistency is a relaxed consistency model that guarantees that,...

  16. 1.15
    Consistency Levels In Cassandra

    This section explores the various consistency levels in Cassandra, detailing...

  17. 1.16
    Consistency Solutions (General Techniques)

    This section explores the general techniques used to achieve consistency in...

  18. 2
    Design Of Hbase: A Distributed Column-Oriented Database On Hdfs

    Apache HBase is a distributed, column-oriented database that operates on...

  19. 2.1
    What Is Hbase?

    HBase is a distributed, non-relational database modeled after Google's...

  20. 2.2
    Hbase Architecture

    This section outlines HBase architecture, highlighting its components, data...

  21. 2.3
    Hbase Components (Detailed)

    This section details the components of HBase, emphasizing its architecture,...

  22. 2.4
    Data Model (Hbase Specifics)

    This section covers the data model of HBase, highlighting its architecture,...

  23. 2.5
    Storage Hierarchy

    This section discusses the storage hierarchy in HBase, covering its...

  24. 2.6
    Cross-Datacenter Replication

    Cross-datacenter replication in HBase allows for asynchronous data...

  25. 2.7
    Auto Sharding And Distribution

    This section covers auto sharding and distribution techniques in HBase,...

  26. 2.8
    Bloom Filter (In Hbase)

    Bloom filters in HBase are probabilistic data structures that determine...

  27. 2.9
    Fold, Store, And Shift (A Conceptual Summary Of Hbase's Write And Read Paths)

    The section outlines the conceptual processes of writing and reading data in...

What we have learnt

  • Key-Value Stores are designed for massive horizontal scalability and high availability.
  • Apache Cassandra operates with a distributed architecture providing eventual consistency, while HBase offers strong consistency on single-row operations.
  • Distributed systems must balance consistency, availability, and partition tolerance as defined by the CAP theorem.

Key Concepts

-- KeyValue Store
A type of NoSQL database that stores data as a collection of key-value pairs, allowing for flexible data modeling.
-- Eventual Consistency
A consistency model where updates to a data item will eventually propagate such that all replicas reflect the same value over time.
-- Strong Consistency
A consistency model that ensures clients read the most recent write; used in some NoSQL databases like HBase for single-row operations.
-- CAP Theorem
A principle that states it is impossible for a distributed data store to simultaneously provide all three guarantees: Consistency, Availability, and Partition tolerance.

Additional Learning Materials

Supplementary resources to enhance your learning experience.