DynamoDB Fundamentals

Amazon DynamoDB Overview

• Fully managed NoSQL database service offering fast, predictable performance with seamless scalability.
• Stores three geographically distributed replicas of each table to ensure high availability and data durability.
• Synchronously replicates data across 3 facilities (Availability Zones) in a region.

Database Characteristics

• Schema-less and non-relational, functioning as a key-value and document database.
• Serverless architecture; no instances to provision or manage.
• Supports push button scaling to adjust database capacity without downtime.

Data Storage

• Data stored on SSDs, providing very low latency.
• Aggregate size of a single item is limited to 400KB, including keys and attributes.
• Can store pointers to S3 objects exceeding 400KB.

Data Structure

• Tables consist of items; items are composed of attributes (fields/columns).
• Primary keys determine how data is stored and retrieved:
  • Partition key: A unique attribute (e.g., user ID).
  • Composite key: Combination of partition key and sort key.

Partitions

• Data is stored in partitions, automatically managed by DynamoDB.
• Throttling may occur if access patterns exceed 3,000 read capacity units (RCUs) or 1,000 write capacity units (WCUs) for a single partition key value.

Consistency Models

• Two reading consistency types:
  • Eventually consistent reads: Default mode, offers lower latency.
  • Strongly consistent reads: Ensures the latest data, configurable via API parameters.

Transactions

• Supports ACID transactions for coordinated changes across multiple items and tables.
• Uses a transaction write API for grouped operations.

API Operations

• Scan: Reads items and attributes by examining the entire table; can be resource-intensive.
  • Can optimize using ProjectionExpression and filter expressions.
• Query: Searches for items based on primary key attributes with better performance than a scan.

Indexing

• Two types of indexes enhance query efficiency:
  • Local Secondary Index (LSI): Alternative sort key local to the partition key, limited to five per table.
  • Global Secondary Index (GSI): Different partition and sort keys for queries, can be created later.

Capacity Management

• Provisioned Capacity: Users specify RCU and WCU based on expected traffic, can utilize auto scaling.
• On-demand Capacity: Automatically adjusts based on actual workload, ideal for unpredictable traffic.

Performance Optimization

• Throttling occurs if provision limits are exceeded; AWS SDKs automatically retry failed requests.
• Use DynamoDB Accelerator (DAX) for in-memory caching, enhancing read performance significantly.

Data TTL and Streams

• Time To Live (TTL): Automatically deletes expired items without extra costs or resource usage.
• DynamoDB Streams: Captures item-level modifications for 24 hours, allowing near real-time event processing (e.g., via AWS Lambda).

Security and Best Practices

• Uses IAM for authentication and access control; supports identity-based policies.
• Recommendations include keeping item sizes small, and separating frequently and infrequently accessed data.

Scalability and Global Tables

• Global Tables: Multi-region, multi-master configuration for global applications, ensuring low-latency data access.
• Supports automatic replication without partial item support; strongly consistent reads require operations within the same region.### Application Auto Scaling
• Auto Scaling does not automatically reduce provisioned capacity when consumed capacity reaches zero.
• Enabling DynamoDB auto scaling occurs by default when creating a table or global secondary index via the AWS Management Console.

High Availability Approaches for Databases

• Prefer DynamoDB over RDS due to its built-in fault tolerance.
• If DynamoDB is not an option, Amazon Aurora offers redundancy and automatic recovery, making it a strong alternative.
• In scenarios where neither DynamoDB nor Aurora is suitable, selecting Multi-AZ RDS provides enhanced availability.
• Regular RDS snapshots serve as a protection measure against data corruption or failure, with minimal performance impact in Multi-AZ deployments.
• Regional replication is available but lacks strong consistency guarantees.
• For databases hosted on EC2, high availability designs must be implemented manually.

Amazon DynamoDB Overview

• Fully managed NoSQL database service offering fast, predictable performance with seamless scalability.
• Stores three geographically distributed replicas of each table to ensure high availability and data durability.
• Synchronously replicates data across 3 facilities (Availability Zones) in a region.

Database Characteristics

• Schema-less and non-relational, functioning as a key-value and document database.
• Serverless architecture; no instances to provision or manage.
• Supports push button scaling to adjust database capacity without downtime.

Data Storage

• Data stored on SSDs, providing very low latency.
• Aggregate size of a single item is limited to 400KB, including keys and attributes.
• Can store pointers to S3 objects exceeding 400KB.

Data Structure

• Tables consist of items; items are composed of attributes (fields/columns).
• Primary keys determine how data is stored and retrieved:
  • Partition key: A unique attribute (e.g., user ID).
  • Composite key: Combination of partition key and sort key.

Partitions

• Data is stored in partitions, automatically managed by DynamoDB.
• Throttling may occur if access patterns exceed 3,000 read capacity units (RCUs) or 1,000 write capacity units (WCUs) for a single partition key value.

Consistency Models

• Two reading consistency types:
  • Eventually consistent reads: Default mode, offers lower latency.
  • Strongly consistent reads: Ensures the latest data, configurable via API parameters.

Transactions

• Supports ACID transactions for coordinated changes across multiple items and tables.
• Uses a transaction write API for grouped operations.

API Operations

• Scan: Reads items and attributes by examining the entire table; can be resource-intensive.
  • Can optimize using ProjectionExpression and filter expressions.
• Query: Searches for items based on primary key attributes with better performance than a scan.

Indexing

• Two types of indexes enhance query efficiency:
  • Local Secondary Index (LSI): Alternative sort key local to the partition key, limited to five per table.
  • Global Secondary Index (GSI): Different partition and sort keys for queries, can be created later.

Capacity Management

• Provisioned Capacity: Users specify RCU and WCU based on expected traffic, can utilize auto scaling.
• On-demand Capacity: Automatically adjusts based on actual workload, ideal for unpredictable traffic.

Performance Optimization

• Throttling occurs if provision limits are exceeded; AWS SDKs automatically retry failed requests.
• Use DynamoDB Accelerator (DAX) for in-memory caching, enhancing read performance significantly.

Data TTL and Streams

• Time To Live (TTL): Automatically deletes expired items without extra costs or resource usage.
• DynamoDB Streams: Captures item-level modifications for 24 hours, allowing near real-time event processing (e.g., via AWS Lambda).

Security and Best Practices

• Uses IAM for authentication and access control; supports identity-based policies.
• Recommendations include keeping item sizes small, and separating frequently and infrequently accessed data.

Scalability and Global Tables

• Global Tables: Multi-region, multi-master configuration for global applications, ensuring low-latency data access.
• Supports automatic replication without partial item support; strongly consistent reads require operations within the same region.### Application Auto Scaling
• Auto Scaling does not automatically reduce provisioned capacity when consumed capacity reaches zero.
• Enabling DynamoDB auto scaling occurs by default when creating a table or global secondary index via the AWS Management Console.

High Availability Approaches for Databases

• Prefer DynamoDB over RDS due to its built-in fault tolerance.
• If DynamoDB is not an option, Amazon Aurora offers redundancy and automatic recovery, making it a strong alternative.
• In scenarios where neither DynamoDB nor Aurora is suitable, selecting Multi-AZ RDS provides enhanced availability.
• Regular RDS snapshots serve as a protection measure against data corruption or failure, with minimal performance impact in Multi-AZ deployments.
• Regional replication is available but lacks strong consistency guarantees.
• For databases hosted on EC2, high availability designs must be implemented manually.

Amazon DynamoDB Overview

• Fully managed NoSQL database service offering fast, predictable performance with seamless scalability.
• Stores three geographically distributed replicas of each table to ensure high availability and data durability.
• Synchronously replicates data across 3 facilities (Availability Zones) in a region.

Database Characteristics

• Schema-less and non-relational, functioning as a key-value and document database.
• Serverless architecture; no instances to provision or manage.
• Supports push button scaling to adjust database capacity without downtime.

Data Storage

• Data stored on SSDs, providing very low latency.
• Aggregate size of a single item is limited to 400KB, including keys and attributes.
• Can store pointers to S3 objects exceeding 400KB.

Data Structure

• Tables consist of items; items are composed of attributes (fields/columns).
• Primary keys determine how data is stored and retrieved:
  • Partition key: A unique attribute (e.g., user ID).
  • Composite key: Combination of partition key and sort key.

Partitions

• Data is stored in partitions, automatically managed by DynamoDB.
• Throttling may occur if access patterns exceed 3,000 read capacity units (RCUs) or 1,000 write capacity units (WCUs) for a single partition key value.

Consistency Models

• Two reading consistency types:
  • Eventually consistent reads: Default mode, offers lower latency.
  • Strongly consistent reads: Ensures the latest data, configurable via API parameters.

Transactions

• Supports ACID transactions for coordinated changes across multiple items and tables.
• Uses a transaction write API for grouped operations.

API Operations

• Scan: Reads items and attributes by examining the entire table; can be resource-intensive.
  • Can optimize using ProjectionExpression and filter expressions.
• Query: Searches for items based on primary key attributes with better performance than a scan.

Indexing

• Two types of indexes enhance query efficiency:
  • Local Secondary Index (LSI): Alternative sort key local to the partition key, limited to five per table.
  • Global Secondary Index (GSI): Different partition and sort keys for queries, can be created later.

Capacity Management

• Provisioned Capacity: Users specify RCU and WCU based on expected traffic, can utilize auto scaling.
• On-demand Capacity: Automatically adjusts based on actual workload, ideal for unpredictable traffic.

Performance Optimization

• Throttling occurs if provision limits are exceeded; AWS SDKs automatically retry failed requests.
• Use DynamoDB Accelerator (DAX) for in-memory caching, enhancing read performance significantly.

Data TTL and Streams

• Time To Live (TTL): Automatically deletes expired items without extra costs or resource usage.
• DynamoDB Streams: Captures item-level modifications for 24 hours, allowing near real-time event processing (e.g., via AWS Lambda).

Security and Best Practices

• Uses IAM for authentication and access control; supports identity-based policies.
• Recommendations include keeping item sizes small, and separating frequently and infrequently accessed data.

Scalability and Global Tables

• Global Tables: Multi-region, multi-master configuration for global applications, ensuring low-latency data access.
• Supports automatic replication without partial item support; strongly consistent reads require operations within the same region.### Application Auto Scaling
• Auto Scaling does not automatically reduce provisioned capacity when consumed capacity reaches zero.
• Enabling DynamoDB auto scaling occurs by default when creating a table or global secondary index via the AWS Management Console.

High Availability Approaches for Databases

• Prefer DynamoDB over RDS due to its built-in fault tolerance.
• If DynamoDB is not an option, Amazon Aurora offers redundancy and automatic recovery, making it a strong alternative.
• In scenarios where neither DynamoDB nor Aurora is suitable, selecting Multi-AZ RDS provides enhanced availability.
• Regular RDS snapshots serve as a protection measure against data corruption or failure, with minimal performance impact in Multi-AZ deployments.
• Regional replication is available but lacks strong consistency guarantees.
• For databases hosted on EC2, high availability designs must be implemented manually.

Amazon DynamoDB Overview

• Fully managed NoSQL database service offering fast, predictable performance with seamless scalability.
• Stores three geographically distributed replicas of each table to ensure high availability and data durability.
• Synchronously replicates data across 3 facilities (Availability Zones) in a region.

Database Characteristics

• Schema-less and non-relational, functioning as a key-value and document database.
• Serverless architecture; no instances to provision or manage.
• Supports push button scaling to adjust database capacity without downtime.

Data Storage

• Data stored on SSDs, providing very low latency.
• Aggregate size of a single item is limited to 400KB, including keys and attributes.
• Can store pointers to S3 objects exceeding 400KB.

Data Structure

• Tables consist of items; items are composed of attributes (fields/columns).
• Primary keys determine how data is stored and retrieved:
  • Partition key: A unique attribute (e.g., user ID).
  • Composite key: Combination of partition key and sort key.

Partitions

• Data is stored in partitions, automatically managed by DynamoDB.
• Throttling may occur if access patterns exceed 3,000 read capacity units (RCUs) or 1,000 write capacity units (WCUs) for a single partition key value.

Consistency Models

• Two reading consistency types:
  • Eventually consistent reads: Default mode, offers lower latency.
  • Strongly consistent reads: Ensures the latest data, configurable via API parameters.

Transactions

• Supports ACID transactions for coordinated changes across multiple items and tables.
• Uses a transaction write API for grouped operations.

API Operations

• Scan: Reads items and attributes by examining the entire table; can be resource-intensive.
  • Can optimize using ProjectionExpression and filter expressions.
• Query: Searches for items based on primary key attributes with better performance than a scan.

Indexing

• Two types of indexes enhance query efficiency:
  • Local Secondary Index (LSI): Alternative sort key local to the partition key, limited to five per table.
  • Global Secondary Index (GSI): Different partition and sort keys for queries, can be created later.

Capacity Management

• Provisioned Capacity: Users specify RCU and WCU based on expected traffic, can utilize auto scaling.
• On-demand Capacity: Automatically adjusts based on actual workload, ideal for unpredictable traffic.

Performance Optimization

• Throttling occurs if provision limits are exceeded; AWS SDKs automatically retry failed requests.
• Use DynamoDB Accelerator (DAX) for in-memory caching, enhancing read performance significantly.

Data TTL and Streams

• Time To Live (TTL): Automatically deletes expired items without extra costs or resource usage.
• DynamoDB Streams: Captures item-level modifications for 24 hours, allowing near real-time event processing (e.g., via AWS Lambda).

Security and Best Practices

• Uses IAM for authentication and access control; supports identity-based policies.
• Recommendations include keeping item sizes small, and separating frequently and infrequently accessed data.

Scalability and Global Tables

• Global Tables: Multi-region, multi-master configuration for global applications, ensuring low-latency data access.
• Supports automatic replication without partial item support; strongly consistent reads require operations within the same region.### Application Auto Scaling
• Auto Scaling does not automatically reduce provisioned capacity when consumed capacity reaches zero.
• Enabling DynamoDB auto scaling occurs by default when creating a table or global secondary index via the AWS Management Console.

High Availability Approaches for Databases

• Prefer DynamoDB over RDS due to its built-in fault tolerance.
• If DynamoDB is not an option, Amazon Aurora offers redundancy and automatic recovery, making it a strong alternative.
• In scenarios where neither DynamoDB nor Aurora is suitable, selecting Multi-AZ RDS provides enhanced availability.
• Regular RDS snapshots serve as a protection measure against data corruption or failure, with minimal performance impact in Multi-AZ deployments.
• Regional replication is available but lacks strong consistency guarantees.
• For databases hosted on EC2, high availability designs must be implemented manually.

Amazon DynamoDB Overview

• Fully managed NoSQL database service offering fast, predictable performance with seamless scalability.
• Stores three geographically distributed replicas of each table to ensure high availability and data durability.
• Synchronously replicates data across 3 facilities (Availability Zones) in a region.

Database Characteristics

• Schema-less and non-relational, functioning as a key-value and document database.
• Serverless architecture; no instances to provision or manage.
• Supports push button scaling to adjust database capacity without downtime.

Data Storage

• Data stored on SSDs, providing very low latency.
• Aggregate size of a single item is limited to 400KB, including keys and attributes.
• Can store pointers to S3 objects exceeding 400KB.

Data Structure

• Tables consist of items; items are composed of attributes (fields/columns).
• Primary keys determine how data is stored and retrieved:
  • Partition key: A unique attribute (e.g., user ID).
  • Composite key: Combination of partition key and sort key.

Partitions

• Data is stored in partitions, automatically managed by DynamoDB.
• Throttling may occur if access patterns exceed 3,000 read capacity units (RCUs) or 1,000 write capacity units (WCUs) for a single partition key value.

Consistency Models

• Two reading consistency types:
  • Eventually consistent reads: Default mode, offers lower latency.
  • Strongly consistent reads: Ensures the latest data, configurable via API parameters.

Transactions

• Supports ACID transactions for coordinated changes across multiple items and tables.
• Uses a transaction write API for grouped operations.

API Operations

• Scan: Reads items and attributes by examining the entire table; can be resource-intensive.
  • Can optimize using ProjectionExpression and filter expressions.
• Query: Searches for items based on primary key attributes with better performance than a scan.

Indexing

• Two types of indexes enhance query efficiency:
  • Local Secondary Index (LSI): Alternative sort key local to the partition key, limited to five per table.
  • Global Secondary Index (GSI): Different partition and sort keys for queries, can be created later.

Capacity Management

• Provisioned Capacity: Users specify RCU and WCU based on expected traffic, can utilize auto scaling.
• On-demand Capacity: Automatically adjusts based on actual workload, ideal for unpredictable traffic.

Performance Optimization

• Throttling occurs if provision limits are exceeded; AWS SDKs automatically retry failed requests.
• Use DynamoDB Accelerator (DAX) for in-memory caching, enhancing read performance significantly.

Data TTL and Streams

• Time To Live (TTL): Automatically deletes expired items without extra costs or resource usage.
• DynamoDB Streams: Captures item-level modifications for 24 hours, allowing near real-time event processing (e.g., via AWS Lambda).

Security and Best Practices

• Uses IAM for authentication and access control; supports identity-based policies.
• Recommendations include keeping item sizes small, and separating frequently and infrequently accessed data.

Scalability and Global Tables

• Global Tables: Multi-region, multi-master configuration for global applications, ensuring low-latency data access.
• Supports automatic replication without partial item support; strongly consistent reads require operations within the same region.### Application Auto Scaling
• Auto Scaling does not automatically reduce provisioned capacity when consumed capacity reaches zero.
• Enabling DynamoDB auto scaling occurs by default when creating a table or global secondary index via the AWS Management Console.

High Availability Approaches for Databases

• Prefer DynamoDB over RDS due to its built-in fault tolerance.
• If DynamoDB is not an option, Amazon Aurora offers redundancy and automatic recovery, making it a strong alternative.
• In scenarios where neither DynamoDB nor Aurora is suitable, selecting Multi-AZ RDS provides enhanced availability.
• Regular RDS snapshots serve as a protection measure against data corruption or failure, with minimal performance impact in Multi-AZ deployments.
• Regional replication is available but lacks strong consistency guarantees.
• For databases hosted on EC2, high availability designs must be implemented manually.

Amazon DynamoDB Overview

• Fully managed NoSQL database service offering fast, predictable performance with seamless scalability.
• Stores three geographically distributed replicas of each table to ensure high availability and data durability.
• Synchronously replicates data across 3 facilities (Availability Zones) in a region.

Database Characteristics

• Schema-less and non-relational, functioning as a key-value and document database.
• Serverless architecture; no instances to provision or manage.
• Supports push button scaling to adjust database capacity without downtime.

Data Storage

• Data stored on SSDs, providing very low latency.
• Aggregate size of a single item is limited to 400KB, including keys and attributes.
• Can store pointers to S3 objects exceeding 400KB.

Data Structure

• Tables consist of items; items are composed of attributes (fields/columns).
• Primary keys determine how data is stored and retrieved:
  • Partition key: A unique attribute (e.g., user ID).
  • Composite key: Combination of partition key and sort key.

Partitions

• Data is stored in partitions, automatically managed by DynamoDB.
• Throttling may occur if access patterns exceed 3,000 read capacity units (RCUs) or 1,000 write capacity units (WCUs) for a single partition key value.

Consistency Models

• Two reading consistency types:
  • Eventually consistent reads: Default mode, offers lower latency.
  • Strongly consistent reads: Ensures the latest data, configurable via API parameters.

Transactions

• Supports ACID transactions for coordinated changes across multiple items and tables.
• Uses a transaction write API for grouped operations.

API Operations

• Scan: Reads items and attributes by examining the entire table; can be resource-intensive.
  • Can optimize using ProjectionExpression and filter expressions.
• Query: Searches for items based on primary key attributes with better performance than a scan.

Indexing

• Two types of indexes enhance query efficiency:
  • Local Secondary Index (LSI): Alternative sort key local to the partition key, limited to five per table.
  • Global Secondary Index (GSI): Different partition and sort keys for queries, can be created later.

Capacity Management

• Provisioned Capacity: Users specify RCU and WCU based on expected traffic, can utilize auto scaling.
• On-demand Capacity: Automatically adjusts based on actual workload, ideal for unpredictable traffic.

Performance Optimization

• Throttling occurs if provision limits are exceeded; AWS SDKs automatically retry failed requests.
• Use DynamoDB Accelerator (DAX) for in-memory caching, enhancing read performance significantly.

Data TTL and Streams

• Time To Live (TTL): Automatically deletes expired items without extra costs or resource usage.
• DynamoDB Streams: Captures item-level modifications for 24 hours, allowing near real-time event processing (e.g., via AWS Lambda).

Security and Best Practices

• Uses IAM for authentication and access control; supports identity-based policies.
• Recommendations include keeping item sizes small, and separating frequently and infrequently accessed data.

Scalability and Global Tables

• Global Tables: Multi-region, multi-master configuration for global applications, ensuring low-latency data access.
• Supports automatic replication without partial item support; strongly consistent reads require operations within the same region.### Application Auto Scaling
• Auto Scaling does not automatically reduce provisioned capacity when consumed capacity reaches zero.
• Enabling DynamoDB auto scaling occurs by default when creating a table or global secondary index via the AWS Management Console.

High Availability Approaches for Databases

• Prefer DynamoDB over RDS due to its built-in fault tolerance.
• If DynamoDB is not an option, Amazon Aurora offers redundancy and automatic recovery, making it a strong alternative.
• In scenarios where neither DynamoDB nor Aurora is suitable, selecting Multi-AZ RDS provides enhanced availability.
• Regular RDS snapshots serve as a protection measure against data corruption or failure, with minimal performance impact in Multi-AZ deployments.
• Regional replication is available but lacks strong consistency guarantees.
• For databases hosted on EC2, high availability designs must be implemented manually.

Amazon DynamoDB Overview

• Fully managed NoSQL database service offering fast, predictable performance with seamless scalability.
• Stores three geographically distributed replicas of each table to ensure high availability and data durability.
• Synchronously replicates data across 3 facilities (Availability Zones) in a region.

Database Characteristics

• Schema-less and non-relational, functioning as a key-value and document database.
• Serverless architecture; no instances to provision or manage.
• Supports push button scaling to adjust database capacity without downtime.

Data Storage

• Data stored on SSDs, providing very low latency.
• Aggregate size of a single item is limited to 400KB, including keys and attributes.
• Can store pointers to S3 objects exceeding 400KB.

Data Structure

• Tables consist of items; items are composed of attributes (fields/columns).
• Primary keys determine how data is stored and retrieved:
  • Partition key: A unique attribute (e.g., user ID).
  • Composite key: Combination of partition key and sort key.

Partitions

• Data is stored in partitions, automatically managed by DynamoDB.
• Throttling may occur if access patterns exceed 3,000 read capacity units (RCUs) or 1,000 write capacity units (WCUs) for a single partition key value.

Consistency Models

• Two reading consistency types:
  • Eventually consistent reads: Default mode, offers lower latency.
  • Strongly consistent reads: Ensures the latest data, configurable via API parameters.

Transactions

• Supports ACID transactions for coordinated changes across multiple items and tables.
• Uses a transaction write API for grouped operations.

API Operations

• Scan: Reads items and attributes by examining the entire table; can be resource-intensive.
  • Can optimize using ProjectionExpression and filter expressions.
• Query: Searches for items based on primary key attributes with better performance than a scan.

Indexing

• Two types of indexes enhance query efficiency:
  • Local Secondary Index (LSI): Alternative sort key local to the partition key, limited to five per table.
  • Global Secondary Index (GSI): Different partition and sort keys for queries, can be created later.

Capacity Management

• Provisioned Capacity: Users specify RCU and WCU based on expected traffic, can utilize auto scaling.
• On-demand Capacity: Automatically adjusts based on actual workload, ideal for unpredictable traffic.

Performance Optimization

• Throttling occurs if provision limits are exceeded; AWS SDKs automatically retry failed requests.
• Use DynamoDB Accelerator (DAX) for in-memory caching, enhancing read performance significantly.

Data TTL and Streams

• Time To Live (TTL): Automatically deletes expired items without extra costs or resource usage.
• DynamoDB Streams: Captures item-level modifications for 24 hours, allowing near real-time event processing (e.g., via AWS Lambda).

Security and Best Practices

• Uses IAM for authentication and access control; supports identity-based policies.
• Recommendations include keeping item sizes small, and separating frequently and infrequently accessed data.

Scalability and Global Tables

• Global Tables: Multi-region, multi-master configuration for global applications, ensuring low-latency data access.
• Supports automatic replication without partial item support; strongly consistent reads require operations within the same region.### Application Auto Scaling
• Auto Scaling does not automatically reduce provisioned capacity when consumed capacity reaches zero.
• Enabling DynamoDB auto scaling occurs by default when creating a table or global secondary index via the AWS Management Console.

High Availability Approaches for Databases

• Prefer DynamoDB over RDS due to its built-in fault tolerance.
• If DynamoDB is not an option, Amazon Aurora offers redundancy and automatic recovery, making it a strong alternative.
• In scenarios where neither DynamoDB nor Aurora is suitable, selecting Multi-AZ RDS provides enhanced availability.
• Regular RDS snapshots serve as a protection measure against data corruption or failure, with minimal performance impact in Multi-AZ deployments.
• Regional replication is available but lacks strong consistency guarantees.
• For databases hosted on EC2, high availability designs must be implemented manually.