Azure Cosmos DB Overview
Azure Cosmos DB is a globally distributed, multi-model database service that enables you to harness the benefits of geographic distribution, elastic scaling, and rich query capabilities for your mission-critical applications.
Introduction
Azure Cosmos DB is Microsoft's globally distributed, multi-model database service. It offers an enterprise-grade, fully managed NoSQL database that supports document, key-value, graph, and column-family data models, along with the Azure Cosmos DB for MongoDB API, Azure Cosmos DB for Cassandra API, Azure Cosmos DB for Gremlin API, and Azure Cosmos DB for Table API.
It is designed for modern applications requiring low latency, high availability, and elastic scalability. Cosmos DB provides a set of APIs to interact with data, allowing developers to choose the API that best suits their application's needs.
Key Features
Global Distribution
Distribute your data across any number of Azure regions worldwide. Read and write operations are routed to the nearest region for low latency access.
Elastic Scalability
Independently and elastically scale throughput and storage on demand. Scale up or down as your application's needs change, without downtime.
Guaranteed Low Latency
Achieve single-digit millisecond latency for both reads and writes at the 99th percentile, anywhere in the world.
Multiple APIs
Support for multiple data models and APIs: SQL (Core), MongoDB, Cassandra, Gremlin, and Table.
Tunable Consistency Models
Choose from five well-defined consistency levels (Strong, Bounded Staleness, Session, Consistent Prefix, Eventual) to balance consistency, availability, and performance.
High Availability
Automatic failover and data replication ensure high availability and disaster recovery capabilities.
Data Models
Azure Cosmos DB is a multi-model database, supporting various data models:
- Document: Store and query JSON documents. Ideal for content management, user profiles, and catalogs.
- Key-Value: Simple key-value storage for session state, user preferences, and caching.
- Graph: Store and query graph relationships. Useful for social networks, recommendation engines, and fraud detection.
- Column-Family: Store and query data with wide-column flexibility. Suitable for time-series data and IoT.
These models are accessible through various APIs, including the SQL (Core) API, which is the native API for Cosmos DB.
Performance and Scalability
Cosmos DB offers predictable performance with guaranteed throughput (Request Units per second - RU/s) and storage. You can scale these resources independently, allowing you to adapt to changing application demands without impacting performance.
Throughput can be provisioned:
- Manually: Set a fixed RU/s value.
- Autoscale: Let Cosmos DB automatically scale throughput based on workload.
Storage scales automatically as you add data to your containers.
Global Distribution
Azure Cosmos DB's core feature is its ability to distribute data globally. You can enable a database account for multi-master writes and have data replicated to any number of Azure regions. This ensures:
- Low Latency: Users experience fast response times as data is served from the nearest region.
- High Availability: Applications remain available even if an entire region experiences an outage.
- Disaster Recovery: Data is resilient and can be recovered in case of regional failures.
Consistency Models
Cosmos DB provides a comprehensive set of five distinct consistency levels, allowing you to strike the right balance between consistency, availability, and performance for your specific application needs:
- Strong: All reads are guaranteed to return the most up-to-date data. Highest consistency, but can incur higher latency and lower availability in distributed scenarios.
- Bounded Staleness: Reads are guaranteed to be no more than a specified number of versions or time interval behind the write.
- Session: The default consistency level. Guarantees that reads within the same client session are consistent.
- Consistent Prefix: Guarantees that reads will return a prefix of all the writes, and no later writes will be returned without all preceding writes.
- Eventual: The weakest consistency. Reads may return stale data, but will eventually be updated with the latest writes. Highest availability and lowest latency.
Common Use Cases
Azure Cosmos DB is well-suited for a wide range of applications:
- IoT Data: Ingesting and processing massive amounts of telemetry data from devices.
- Web and Mobile Apps: Storing user profiles, shopping carts, and session data.
- Gaming: Storing player data, leaderboards, and game state.
- Real-time Analytics: Powering dashboards and insights from rapidly changing data.
- E-commerce: Managing product catalogs, orders, and customer data.
- Personalization: Building recommendation engines and personalized user experiences.
Getting Started
To start using Azure Cosmos DB:
- Create an Azure Cosmos DB Account: Through the Azure portal, CLI, or SDKs.
- Choose an API: Select the API that best fits your application (SQL, MongoDB, Cassandra, etc.).
- Create a Database and Container: Define your data structure.
- Ingest Data: Add your data to the container.
- Query Data: Use the chosen API's query language (e.g., SQL for the Core API) to retrieve and manipulate data.
Explore the official Azure Cosmos DB documentation for detailed guides, tutorials, and API references.