Data Partitioning

Strategies:

Range-based Partitioning: Divides data based on a specific range (e.g., splitting data by user IDs or timestamps). Effective for queries that involve ranges but can lead to uneven data distribution.
Hash-based Partitioning: Assigns data to nodes using a hash function on the key. Offers even distribution but may lead to data hotspots if keys are not uniformly distributed.
Consistent Hashing: Utilizes a hash function to map both data items and storage nodes onto a ring structure, reducing the impact of node additions or removals on data distribution.

Considerations:

Balanced Distribution: Ensuring that each partition or shard has a similar amount of data to prevent uneven loads on nodes.
Rebalancing: Strategies to redistribute data when new nodes are added or existing ones are removed without causing significant disruptions.

Data Replication

Replication Techniques:

Primary-Backup Replication: One node (primary) handles write operations and replicates data to backup nodes for fault tolerance.
Multi-master Replication: Allows multiple nodes to accept write operations, requiring synchronization to maintain consistency across replicas.

Challenges and Solutions:

Consistency Maintenance: Ensuring that replicas remain consistent despite concurrent updates.
Conflict Resolution: Resolving conflicts that arise when multiple replicas receive conflicting updates.

Consistency

Consistency Models:

Strong Consistency: Guarantees that all replicas have the same data at the same time. Achieved by synchronously updating all replicas.
Eventual Consistency: Permits temporary inconsistencies but guarantees that all replicas will converge to the same state eventually.
Causal Consistency: Ensures causal relationships between related updates while allowing some degree of inconsistency.

Trade-offs:

Performance vs. Consistency: Stronger consistency models often come with increased latency and reduced performance compared to weaker consistency models.

Inconsistency Resolution

Conflict Resolution Techniques:

Last Write Wins: Simple but may lead to data loss or inconsistency in certain scenarios.
Vector Clocks: Assigns a unique identifier to each update, enabling conflict resolution based on causality.
Merge Strategies: Merges conflicting updates based on predefined rules or application-specific logic.

Handling Conflicts:

Automatic vs. Manual Conflict Resolution: Systems can automatically resolve conflicts based on predefined rules or involve manual intervention to resolve complex conflicts.

Handling Failures

Failure Detection:

Heartbeats and Timeout Mechanisms: Nodes periodically send heartbeats to indicate their status; timeouts are used to detect unresponsive nodes.

Failure Recovery:

Replica Replacement: When a node fails, replicas are promoted or new replicas are created to maintain the desired level of redundancy.

System Architecture Diagram

Components:

Nodes and Clusters: Illustrates the arrangement of individual nodes and how they form a cluster.
Replication Topology: Indicates the replication strategy employed, such as primary-backup or multi-master.

Write Path

Steps:

Data Validation: Checking data integrity and ensuring it meets defined constraints before storage.
Selection of Storage Node: Determining the appropriate node or partition to store the data based on the partitioning strategy.
Replication: If required, replicating the data to other nodes according to the replication strategy.

Read Path