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AWS DynamoDB vs Azure CosmosDB vs GCP Bigtable & Firestore

AWS NoSQL vs Azure NoSQL vs GCP NoSQL

AWS vs NoSQL vs GCP NoSQL

Feature Amazon Azure Cosmos DB Google Firestore Google Cloud
Data Model Primarily Key-Value and Document Multi-model: Document, Key-Value, Wide-Column (Cassandra API), (Gremlin API), Table (Table API) Document-oriented Wide-column (Column-family)
Scalability Highly scalable, automatic partitioning (Partitioning) Massively scalable, automatic and instant scalability with global distribution options (Partitioning) Highly scalable, automatic scaling (Add Data – scaling is implicit) Massively scalable, horizontal scaling via nodes (Scalability)
Global Distribution Multi-region, multi-active with Global Tables Built-in global distribution with multi-region writes (multi-master) available (Global Data Distribution) Multi-region with strong consistency options (Locations) Global replication available (Replication Overview)
Consistency Tunable (Read Consistency): Eventual, Strong Five well-defined models (Consistency Levels): Strong, Bounded Staleness, Session, Consistent Prefix, Eventual Tunable (Transactions – implies strong), Eventual Strong consistency per row (Consistency)
Querying Key-based lookups, Scan, Query API with limited filtering -like (SQL Query) for document model, -specific for others Rich querying with indexing, including compound indexes Key-based lookups, range scans, filtering on columns
Transactions ACID transactions (multi-item) (Transactions) ACID transactions across documents within a partition (Transactions) ACID transactions (multi-document) (Transactions) Transactions within a single row (Transactions)
Serverless Fully serverless, auto-scaling to zero (On-Demand Pricing) Fully managed with serverless options and provisioned throughput with auto-scaling Fully serverless, pay-per-use (Firebase Pricing) Not fully serverless, billed by node hours (Pricing)
APIs/Ecosystem AWS ecosystem integration (AWS) Broad API support, strong Azure integration (Azure), integration with Microsoft Fabric GCP ecosystem integration (Google Cloud), Firebase integration GCP ecosystem integration (Google Cloud), HBase compatibility
Pricing Provisioned (Provisioned Pricing) and On-demand based on RCUs/WCUs and storage Provisioned Throughput (Provisioned Pricing) and Serverless based on request units, storage, and bandwidth Pay-per-read, pay-per-write, pay-per-storage (Firebase Pricing) Billed by node hours, storage, and network egress (Pricing)
Indexing Primary key (partition and sort key), Global Secondary Indexes (GSIs), Local Secondary Indexes (LSIs) Automatic indexing of all attributes by default, with options to customize (Index Policy) Automatic indexing with options for composite and single-field indexes Row key, column families, and qualifiers are indexed (Schema Design – key is crucial for querying)
Managed Services Fully managed (Features) Fully managed (Overview), handles patching, upgrades, backups, global replication Fully managed (Overview), handles patching, upgrades, backups, multi-region Fully managed (Overview), handles patching, upgrades, backups, replication

Key Differences and Considerations:

  • Data Model Flexibility: Azure Cosmos DB (Introduction) offers the most built-in flexibility with its multi-model support.
  • Querying Power: Cosmos DB’s SQL-like querying (SQL Query) and Firestore’s rich indexing (Firestore Indexing) provide powerful ways to retrieve data. DynamoDB’s querying (Query API) is more structured. Bigtable’s querying (Reads) is focused on key-based and range scans.
  • Global Distribution: Both Cosmos DB (Global Data Distribution) and DynamoDB (Global Tables) offer robust global distribution. Firestore (Locations) provides multi-region options, and Bigtable (Replication Overview) offers global replication.
  • Serverless Nature: DynamoDB (On-Demand Pricing), Azure Cosmos DB (Serverless), and Cloud Firestore (Firebase Pricing) offer serverless options. Bigtable (Pricing) requires managing nodes.
  • : The best choice depends on your specific application needs. Refer to the documentation links in the table for typical use cases of each service.
  • Ecosystem Integration: Consider your existing cloud provider and the ease of integration with other services.

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