description Cosmos DB (Azure) Overview
Azure Cosmos DB is a globally distributed, multi-model database service from Microsoft. It offers unparalleled scalability and performance, supporting various data models including document, key-value, graph, and column-family. Its global distribution and flexible query language make it suitable for diverse applications, from web and mobile apps to IoT and gaming.
help Cosmos DB (Azure) FAQ
What APIs and data models does Azure Cosmos DB support?
Azure Cosmos DB supports five API interfaces: the Core (SQL) API for document data, the MongoDB API for MongoDB-compatible workloads, the Cassandra API for wide-column data, the Gremlin API for graph databases, and the Table API for key-value storage. Each API maps to the same underlying partitioned, distributed storage engine, so you can choose the query model that fits your application without changing the back-end infrastructure. This multi-model approach is one of Cosmos DB's primary differentiators from competitors like Amazon DynamoDB.
What consistency levels does Cosmos DB offer, and how do they differ from traditional databases?
Cosmos DB offers five well-defined consistency levels—Strong, Bounded Staleness, Session, Consistent Prefix, and Eventual—exposed as configurable knobs rather than binary choices. Session consistency is the default and guarantees read-your-own-writes within a user session, while Strong consistency provides linearizable reads globally at the cost of higher latency. The ability to trade off consistency for latency and availability at a granular level is a feature most traditional SQL and NoSQL databases do not natively offer.
Does Azure Cosmos DB have a free tier?
Yes, Azure Cosmos DB offers a free tier limited to one account per Azure subscription, which includes the first 400 RU/s of provisioned throughput and 5 GB of storage at no charge. Once those limits are exceeded, standard pricing applies for the additional throughput and storage consumed. The free tier is useful for development, testing, and small production workloads, but is not sufficient for most commercial-scale applications.
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