https://github.com/filonenkodima/distributeddatabases
DistributedDatabases is an educational project focused on the principles and implementation of distributed database systems. The project demonstrate key concepts such as data replication, sharding, consistency models, and fault tolerance in distributed environments.
https://github.com/filonenkodima/distributeddatabases
comserver csharp grpc remlib wcf
Last synced: about 1 month ago
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DistributedDatabases is an educational project focused on the principles and implementation of distributed database systems. The project demonstrate key concepts such as data replication, sharding, consistency models, and fault tolerance in distributed environments.
- Host: GitHub
- URL: https://github.com/filonenkodima/distributeddatabases
- Owner: FilonenkoDima
- Created: 2023-07-02T22:58:10.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-08-28T16:42:32.000Z (almost 2 years ago)
- Last Synced: 2025-02-13T19:40:45.586Z (over 1 year ago)
- Topics: comserver, csharp, grpc, remlib, wcf
- Language: C#
- Homepage:
- Size: 1.27 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# DistributedDatabases
## About the Project
DistributedDatabases is an educational project designed to explore the core concepts of distributed database systems. This project covers various aspects of distributed databases, including data replication, sharding, consistency models, and fault tolerance. Through practical examples and exercises, the project aims to provide a comprehensive understanding of how distributed databases operate in real-world scenarios.
## Purpose of the Project
- Gained an in-depth understanding of distributed database concepts and architectures.
- Implemented data replication techniques to ensure high availability and reliability.
- Explored sharding strategies to distribute data across multiple nodes for scalability.
- Analyzed consistency models and trade-offs between strong and eventual consistency.
- Demonstrated fault tolerance mechanisms to maintain system availability during failures.
## Key Concepts Covered
- Data Replication: Techniques for replicating data across multiple nodes to ensure availability.
- Sharding: Strategies for partitioning data across different servers to improve scalability.
- Consistency Models: Exploration of different consistency models, including strong, eventual, and causal consistency.
- Fault Tolerance: Mechanisms to ensure system reliability and availability during network partitions or node failures.
- Distributed Query Processing: Techniques for efficiently querying data across distributed systems.