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Use Cosmos DB NoSQL API for Project

  • Status: Proposed
  • Date: 2024-10-17
  • Work Item: 1234-Select-CosmosDB-API

Context and Problem

Our team needs to select the most suitable Cosmos DB API for our new data-intensive application. The chosen API must support high scalability, flexible schema, and performance for large datasets. We are considering the options provided by Azure Cosmos DB: NoSQL, MongoDB, Cassandra, PostgreSQL, and Gremlin (Graph).

Decision Drivers

  • Performance Requirements: Must handle high throughput and low latency.
  • Flexibility of Schema: Ability to adjust data models as requirements evolve.
  • Query Complexity: Need to support complex queries and transactions.
  • Compatibility: Must integrate well with existing tools and technologies.

Considered Options

  • Cosmos DB NoSQL
  • Cosmos DB MongoDB API
  • Cosmos DB Cassandra API
  • Cosmos DB PostgreSQL API
  • Cosmos DB Gremlin API

Decision Outcome

Chosen option: Cosmos DB NoSQL, because it offers the best balance of flexibility, performance, and integration capabilities.

Consequences

  • Good, because it provides high throughput and low latency, essential for our data-intensive application.
  • Good, because it offers flexible schema support, allowing us to adapt our data models as requirements change.
  • Bad, because it may require additional effort to translate some existing MongoDB queries.

Implementation

  1. Develop a migration plan for existing data.
  2. Update the application to use the Cosmos DB NoSQL API.
  3. Perform extensive testing to ensure performance and compatibility.
  4. Monitor and optimize the database during the initial deployment phase.

Confirmation

Confirm implementation by:

  1. Running performance benchmarks.
  2. Conducting schema validation checks.
  3. Verifying integration with existing tools and applications.

Stakeholders

  • Development Team
  • Database Administrators
  • Product Owners
  • DevOps Team

Pros and Cons of the Options

Cosmos DB NoSQL

  • Good, because it provides high performance and scalability.
  • Good, because it offers flexible schema.
  • Neutral, because it integrates well with existing Azure tools.
  • Bad, because it may require additional effort to translate existing queries.

Cosmos DB MongoDB API

  • Good, because it supports MongoDB queries natively.
  • Good, because it offers flexibility in schema.
  • Neutral, because of moderate performance for high throughput.
  • Bad, because it may not handle certain complex queries efficiently.

Cosmos DB Cassandra API

  • Good, because it provides high availability and scalability across multiple regions.
  • Good, because it supports wide-column stores, making it great for write-heavy workloads.
  • Neutral, because it has consistent performance with large datasets.
  • Bad, because it can be complex to manage and requires specific expertise.

Cosmos DB PostgreSQL API

  • Good, because it offers strong ACID compliance for transactional consistency.
  • Good, because it supports advanced querying and indexing capabilities.
  • Neutral, because it integrates well with existing PostgreSQL tools and applications.
  • Bad, because it may not scale as efficiently for very high-throughput scenarios.

Cosmos DB Gremlin API (Graph)

  • Good, because it excels at handling complex relationships and graph-based queries.
  • Good, because it supports traversing large graphs quickly.
  • Neutral, because it offers flexibility for graph-based data models.
  • Bad, because it has a steeper learning curve and may not be ideal for non-graph data.

More Information

No more information available.

Follow-On Information

The decision will be reviewed quarterly to ensure it continues to meet performance and scalability requirements. Updates or revisions will be documented as needed.

Record History

  • Proposed: 2024-10-15
  • Rejected: [Date, if applicable]
  • Accepted: [Date, if applicable]
  • Last Reviewed: [Date, if appliable]
  • Deprecated: [Date, if applicable]
  • Superseded by: [Reference to the ADR that supersedes this one, if applicable]
  • Date Superseded: [Date, if applicable]
  • Archived: [Date, if applicable]