Distributed Data Storage
Using a network of nodes across various locations, it prevents data congestion and enhances accessibility, with essential components such as..
- Distributed File Systems: Technologies such as Hadoop Distributed File System (HDFS), Google File System (GFS), and Amazon S3 allow for distributing large files across tens of nodes that are fault-tolerant and have a high rate of throughput.
- NoSQL Databases: Cassandra, MongoDB, and Couchbase represent distributed data storage. They are suitable for large-scale projects because of their high availability and flexible data models.
- Key-Value Stores: Resource-Redis, Riak, and Dynamo systems support key-value storage that is replicated with easy distribution and partitioning, rich enough for caching and looking for data accessed frequently.
Components of Distributed System
Many modern computing platforms, such as Internet applications or systems, are built on distributed systems, which function as essential infrastructure.
- These systems feature good scalability, fault tolerances, and application flexibility, which enable them to be used in various areas, including cloud computing, IoT, and big data analytics.
- It is necessary to learn the components of distributed systems, as it would be part of designing, developing, and maintaining faultless or efficient systems.
Important Topics for Components of Distributed System
- Communication Infrastructure
- Distributed Data Storage
- Distributed Computing Models
- Distributed Coordination
- Fault Tolerance Mechanisms
- Scalability Techniques
- Security in Distributed Systems
- Distributed System Monitoring and Management
- Deployment and orchestration
- Integration with Cloud Services
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