DynamoDB

Website

aws.amazon.com

Categories

#Databases #NoSQL Databases #Relational Databases #Cloud Hosting

Azure Cosmos DB

Website

azure.microsoft.com

Categories

#NoSQL Databases #Databases #Graph Databases #Key-Value Database

DynamoDB features and specs

• Scalability
  DynamoDB automatically scales up and down to handle your application's needs, with no intervention required. This allows for easy handling of traffic spikes and growth over time.
• Performance
  With its fast, predictable performance at any scale, DynamoDB ensures low-latency responses, even with large volumes of data.
• Fully Managed
  As a fully managed service, DynamoDB handles hardware provisioning, setup, configuration, replication, software patching, and backups, letting you focus on your application.
• Flexible Data Model
  DynamoDB supports both document and key-value store models, providing flexibility in how you structure your data.
• Security
  DynamoDB integrates with AWS Identity and Access Management (IAM) to provide fine-grained access control and encrypts data at rest and in transit.
• Global Tables
  You can create multi-region, fully replicated tables for high availability and globally distributed apps with low latency reads and writes.
• Event-Driven Architecture
  DynamoDB integrates with AWS Lambda for automatic triggering and the creation of event-driven architectures.

Possible disadvantages of DynamoDB

• Pricing Complexity
  DynamoDB's pricing model, which charges based on read and write capacity units, storage, and data transfer, can be complex and difficult to predict.
• Limited Query Capabilities
  DynamoDB does not support complex queries as well as traditional SQL databases. Querying capabilities are limited primarily to primary key attributes.
• Secondary Indexes
  While DynamoDB supports secondary indexes, their use can be limited and complex to manage effectively compared to relational databases.
• Consistency
  DynamoDB offers eventual consistency by default. While strongly consistent reads are available, they can be more expensive and slower.
• Data Size Limitations
  Each item in a DynamoDB table must be 400KB or less, limiting the amount of data you can store in a single item.
• Vendor Lock-In
  Using DynamoDB heavily ties your application to AWS, which can be a downside if you want to maintain flexibility in your cloud infrastructure choices.

Azure Cosmos DB features and specs

• Global Distribution
  Azure Cosmos DB allows for the distribution of data across multiple global regions, enhancing availability and delivering low-latency access to data for users around the world.
• Multi-Model Support
  It supports multiple data models including document, graph, key-value, and column-family APIs, making it versatile for a variety of applications and use cases.
• Automatic Scaling
  The database automatically scales up and down to meet the demands of application traffic, helping to manage workloads efficiently without manual intervention.
• High Throughput and Low Latency
  Cosmos DB offers high performance with single-digit millisecond read and write latencies, ensuring fast access to data for applications.
• Comprehensive SLAs
  Azure Cosmos DB provides industry-leading SLAs covering availability, throughput, consistency, and latency, offering strong guarantees for customers.
• Integrated Security
  It includes robust security features such as SSL/TLS encryption, role-based access control, and integration with Azure Active Directory for secure data management.

Possible disadvantages of Azure Cosmos DB

• Cost
  Azure Cosmos DB can be expensive, especially for high-throughput workloads and global distribution scenarios. Its pricing model based on provisioned throughput (RU/s) can add up quickly.
• Complexity
  Managing and optimizing Cosmos DB can be complex, requiring a deep understanding of its configuration settings, partitioning strategies, and indexing to achieve optimal performance.
• Vendor Lock-In
  As a proprietary service, using Cosmos DB tightly couples your application to Azure. This can make it difficult to migrate to other database solutions or cloud providers in the future.
• Consistency Models
  Azure Cosmos DB supports multiple consistency levels which can introduce complexity in designing applications. Developers need to understand and choose the appropriate consistency level for their specific use case.
• Limited Native Analytics
  Cosmos DB does not have built-in advanced analytics capabilities. Integrating with other services like Azure Synapse or Databricks may be necessary for sophisticated data analytics and reporting.

#13 - Amazon DynamoDB Basics In Under 5 Minutes [Tutorial For Beginners]

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