- Coverage by target cloud
- How the targets compare
- On Google Cloud, Azure, OCI, and Private Kubernetes
- On Google Cloud
- On Azure
- On OCI
Coverage by target cloud
How the targets compare
Each row compares a capability of DocumentDB (MongoDB) with its adaptation on each target. A dash means this row is not stated for that target.Max adaptation
Runtime surface
Limits
Infrastructure-only adaptation
Runtime surface
Limits
On Google Cloud, Azure, OCI, and Private Kubernetes
Via MongoDB Atlas
How it works
Your application’s MongoDB driver connects directly to MongoDB Atlas. These database requests are the data plane. The driver and MongoDB wire protocol stay unchanged, and Tensor9 does not proxy or translate these database requests. Management requests, such as snapshots, restore, replicas, failover, and configuration changes, form the control plane. Tensor9 serves the DocumentDB API in the customer’s appliance and translates those requests to the target’s management API. The sections below describe which operations have equivalents and which return errors.
Queries reach the database directly; only the management calls are translated.
Database connections
MongoDB Atlas runs MongoDB. It supports multi-document transactions, change streams, correlated lookups, and collation; their behavior and limits follow the selected MongoDB version and Atlas tier. Your driver connects directly to Atlas, where your queries and indexes run. Each target implements a different set of MongoDB features. The comparison table on this page covers transactions, change streams, lookups, text and vector search, and other features your application may use.Database management
At runtime your application and operational tooling keep making the same DocumentDB calls they make today: describe the cluster, take a snapshot, restore to a point in time, add replica instances, pause and resume, change the tier or a parameter. The adapter accepts DocumentDB requests, returns DocumentDB response formats, and performs supported operations through the Atlas Admin API: snapshots and continuous-backup point-in-time restore, replica node layout, cluster pause / resume, and tier and storage changes. DocumentDB’s global-cluster calls map to replica placement across Atlas regions. Atlas also offers geographic sharding, which partitions data by location and is a separate deployment choice. When your product is deployed into the customer environment, Tensor9 compiles the cluster your stack already declares into the equivalent MongoDB Atlas resources and sets the connection string and credentials into your application’s configuration. The control-plane adapter then covers the management calls your running system makes.
Tensor9 translates DocumentDB management requests to the target API and returns DocumentDB responses.
Limitations
△ Where DocumentDB and MongoDB Atlas stay different- Manual failover tests recovery. Atlas elects a new primary automatically; the manual failover call maps to Atlas’s test-failover, useful for verifying resilience rather than day-to-day operations.
- Event subscriptions are not served. DocumentDB event notifications publish to SNS; Atlas alerts are a different model with no direct counterpart.
- DocumentDB-proprietary settings have no counterpart. Standard cluster parameters translate to Atlas cluster configuration; parameters specific to DocumentDB are not supported on the target.
Other considerations
Migration. Copy existing data with MongoDB migration tools that the target supports. Check the workload’s queries, indexes, and BSON types against the comparison table before switching connections; sharing a wire protocol does not make every MongoDB feature equivalent. Operations. The customer owns the Atlas organization: cluster tiers, cloud and region choices, and pricing are MongoDB’s. Features and capacity. The comparison table on this page lists database features and high-availability differences. Check the target service’s pricing and capacity limits when sizing the deployment.On Google Cloud
Via Firestore (MongoDB compatibility)
How it works
Your application’s MongoDB driver connects directly to Firestore with MongoDB compatibility. These database requests are the data plane. The driver and MongoDB wire protocol stay unchanged, and Tensor9 does not proxy or translate these database requests. Management requests, such as snapshots, restore, replicas, failover, and configuration changes, form the control plane. Tensor9 serves the DocumentDB API in the customer’s appliance and translates those requests to the target’s management API. The sections below describe which operations have equivalents and which return errors.
Queries reach the database directly; only the management calls are translated.
Database connections
Firestore with MongoDB compatibility supports the MongoDB 7.0 wire protocol. It manages instance sizing, read scaling, and multi-region high availability. Its MongoDB compatibility has limits: no vector search or collation, many unsupported aggregation stages, and change streams in preview. Your driver connects directly to Firestore. Each target implements a different set of MongoDB features. The comparison table on this page covers transactions, change streams, lookups, text and vector search, and other features your application may use.Database management
At runtime your application and operational tooling keep making the same DocumentDB calls they make today. The adapter accepts DocumentDB requests, returns DocumentDB response formats, and performs supported operations through the Firestore API: on-demand backups, point-in-time recovery within Firestore’s 7-day window, and database-level settings. Much of the rest has nothing to translate to, because Firestore is serverless: reads scale automatically, failover is automatic, and there is no cluster to stop, start, or size. The limitations below identify those operations. Each returns an error. When your product is deployed into the customer environment, Tensor9 compiles the cluster your stack already declares into the equivalent Firestore with MongoDB compatibility resources and sets the connection string and credentials into your application’s configuration. The control-plane adapter then covers the management calls your running system makes.
Tensor9 translates DocumentDB management requests to the target API and returns DocumentDB responses.
Limitations
△ Where DocumentDB and Firestore (Mongo compat) stay different- Serverless operation removes instance controls. There are no replica instances to add, no manual failover, no stop / start, and no compute or storage sizing; reads scale and fail over automatically.
- Multi-region is a create-time choice. The database’s location is fixed at creation; there is no global-cluster object and no switchover call.
- Few cluster settings have equivalents. Database-level settings (point-in-time recovery, delete protection) map; most DocumentDB cluster parameters have no counterpart.
- Event subscriptions are not served. DocumentDB event notifications publish to SNS; Cloud Monitoring is a different model with no direct counterpart.
Other considerations
Migration. Copy existing data with MongoDB migration tools that the target supports. Check the workload’s queries, indexes, and BSON types against the comparison table before switching connections; sharing a wire protocol does not make every MongoDB feature equivalent. Operations. The customer owns the Firestore database in their Google Cloud: quotas and pricing are Google’s. Features and capacity. The comparison table on this page lists database features and high-availability differences. Check the target service’s pricing and capacity limits when sizing the deployment.On Azure
Via Azure Cosmos DB for MongoDB (vCore)
How it works
Your application’s MongoDB driver connects directly to Azure Cosmos DB for MongoDB (vCore). These database requests are the data plane. The driver and MongoDB wire protocol stay unchanged, and Tensor9 does not proxy or translate these database requests. Management requests, such as snapshots, restore, replicas, failover, and configuration changes, form the control plane. Tensor9 serves the DocumentDB API in the customer’s appliance and translates those requests to the target’s management API. The sections below describe which operations have equivalents and which return errors.
Queries reach the database directly; only the management calls are translated.
Database connections
DocumentDB and Cosmos vCore each implement part of the MongoDB API. Cosmos vCore supports graph lookups and more aggregation operations than DocumentDB, but does not support server-side mapReduce. It limits multi-document transactions to 30 seconds. Your driver connects directly to Cosmos vCore, where your queries and indexes run. Each target implements a different set of MongoDB features. The comparison table on this page covers transactions, change streams, lookups, text and vector search, and other features your application may use.Database management
At runtime your application and operational tooling keep making the same DocumentDB calls they make today: describe the cluster, take a snapshot, restore to a point in time, add replicas, trigger a failover, change the tier or a parameter. The adapter accepts DocumentDB requests, returns DocumentDB response formats, and performs supported operations on Azure: snapshots and point-in-time restore to a new cluster, replica clusters, manual failover (forced or graceful promotion), and tier and storage updates. Global-cluster calls map to Cosmos vCore’s single secondary region. When your product is deployed into the customer environment, Tensor9 compiles the cluster your stack already declares into the equivalent Azure Cosmos DB for MongoDB (vCore) resources and sets the connection string and credentials into your application’s configuration. The control-plane adapter then covers the management calls your running system makes.
Tensor9 translates DocumentDB management requests to the target API and returns DocumentDB responses.
Limitations
△ Where DocumentDB and Cosmos DB (vCore) stay different- No stop / start. Cosmos vCore has no pause; a managed cluster runs continuously.
- Only one secondary region is supported. There is no multi-region global-cluster object; cross-region maps to a single secondary region with forced / graceful failover.
- Event subscriptions are not served. DocumentDB event notifications publish to SNS; Azure Monitor is a different model with no direct counterpart.
- DocumentDB-proprietary settings have no counterpart. Standard cluster parameters translate to the cluster’s configuration; parameters specific to DocumentDB are not supported on the target.
Other considerations
Migration. Copy existing data with MongoDB migration tools that the target supports. Check the workload’s queries, indexes, and BSON types against the comparison table before switching connections; sharing a wire protocol does not make every MongoDB feature equivalent. Operations. The customer owns the Cosmos DB cluster in their Azure subscription: maintenance windows, quotas, and pricing are Microsoft’s. Features and capacity. The comparison table on this page lists database features and high-availability differences. Check the target service’s pricing and capacity limits when sizing the deployment.On OCI
Via Oracle Autonomous JSON Database (MongoDB API)
How it works
Your application’s MongoDB driver connects directly to Oracle Autonomous JSON Database. These database requests are the data plane. The driver and MongoDB wire protocol stay unchanged, and Tensor9 does not proxy or translate these database requests. Management requests, such as snapshots, restore, replicas, failover, and configuration changes, form the control plane. Tensor9 serves the DocumentDB API in the customer’s appliance and translates those requests to the target’s management API. The sections below describe which operations have equivalents and which return errors.
Queries reach the database directly; only the management calls are translated.
Database connections
Autonomous JSON Database serves your driver through the Oracle Database API for MongoDB, which supports a MongoDB-4.2-era protocol and executes operations on Oracle’s SQL / JSON engine. Your driver connects directly using a load-balanced connection string. You can also query those collections with SQL, a feature DocumentDB does not offer. Some newer MongoDB features are missing; see the comparison table on this page. Each target implements a different set of MongoDB features. The comparison table on this page covers transactions, change streams, lookups, text and vector search, and other features your application may use.Database management
At runtime your application and operational tooling keep making the same DocumentDB calls they make today. The adapter accepts DocumentDB requests, returns DocumentDB response formats, and performs supported operations on OCI: backups and point-in-time recovery within the retention window, stop / start, and online compute and storage scaling. The operations OCI has no counterpart for are listed under Limitations. Each returns an error. When your product is deployed into the customer environment, Tensor9 compiles the cluster your stack already declares into the equivalent Oracle Autonomous JSON Database resources and sets the connection string and credentials into your application’s configuration. The control-plane adapter then covers the management calls your running system makes.
Tensor9 translates DocumentDB management requests to the target API and returns DocumentDB responses.
Limitations
△ Where DocumentDB and Autonomous JSON Database stay different- No manual failover and no cross-region standby. Autonomous Data Guard is not available for JSON workloads, so there is no failover / switchover call and no global database; cross-region DR is backup copies, refreshable clones, or replication tooling.
- No replica instances. Read scale-out is served by compute auto-scaling (up to 3x), not replicas you add.
- Most cluster settings have no equivalent. Compute and storage scale online; most DocumentDB cluster parameters have no counterpart.
- Event subscriptions are not served. DocumentDB event notifications publish to SNS; OCI Events is a different model with no direct counterpart.