Managed Databases on Azure

This content was generated with the assistance of AI and should be verified against the official documentation before being relied on in production.

See the section bibliography for the reference material consulted while preparing these pages.

This page targets Azure CLI 2.90.0 — re-verify exact command names and current GA/retirement status against the Azure CLI release notes and each linked product page before relying on them, since managed-database offerings and their names have changed more than once in the last few release cycles (Azure Cosmos DB for MongoDB vCore alone was renamed to Azure DocumentDB in late 2025). This is a landing/overview page, not a hands-on walkthrough: for setup steps and CLI examples for a given engine, follow the link in the table below to this section’s own page for it.

Engine-to-Azure-option map

For every database engine this site documents, the table below gives the corresponding Azure option(s), whether each is first-party PaaS, an Azure Native ISV Service, Marketplace SaaS, or self-managed on AKS/VMs, this section’s own page that covers it, and this site’s own engine reference for the database itself.

Engine Azure option(s) Kind This section Engine reference

SQL (SQL Server family / generic SQL)

Azure SQL Database; Azure SQL Managed Instance; SQL Server on Azure VMs

First-party PaaS (Database, Managed Instance) / IaaS (VMs)

Azure SQL

SQL Reference

PostgreSQL / pgvector

Azure Database for PostgreSQL flexible server (+ elastic clusters)

First-party PaaS

PostgreSQL and MySQL on Azure

PostgreSQL & pgvector

MySQL

Azure Database for MySQL flexible server

First-party PaaS

PostgreSQL and MySQL on Azure

SQL Reference

MongoDB

Azure DocumentDB (formerly Cosmos DB for MongoDB vCore); Azure Cosmos DB for MongoDB (RU); MongoDB Atlas on Azure (Marketplace)

First-party PaaS (DocumentDB, Cosmos DB) / Marketplace SaaS (Atlas)

Cosmos DB and Azure DocumentDB

MongoDB Reference

Redis

Azure Managed Redis; Azure Cache for Redis (retiring); Redis Cloud

First-party PaaS (Managed Redis, Cache for Redis) / Marketplace SaaS (Redis Cloud)

Redis and Partner Databases on Azure

Redis Reference

Elasticsearch

Elastic Cloud (Azure Native ISV Service, az elastic); self-managed ECK on AKS

Azure Native ISV Service / self-managed (AKS)

Redis and Partner Databases on Azure

Elasticsearch Reference

Couchbase

Couchbase Capella (Marketplace); Autonomous Operator on AKS

Marketplace SaaS / self-managed (AKS)

Redis and Partner Databases on Azure

Couchbase Reference

Neo4j

Neo4j AuraDB (Marketplace); Helm chart on AKS

Marketplace SaaS / self-managed (AKS)

Redis and Partner Databases on Azure

Neo4j Reference

Qdrant

Qdrant Cloud (Marketplace, Azure regions); Helm chart on AKS

Marketplace SaaS / self-managed (AKS)

Redis and Partner Databases on Azure

Qdrant Reference

Solr / Lucene

Self-managed on AKS (Solr Operator) or VMs; Azure AI Search as the managed alternative

Self-managed (AKS/VMs) / first-party PaaS (AI Search, as an alternative rather than a hosted Solr/Lucene)

Redis and Partner Databases on Azure

Apache Solr Reference / Apache Lucene Reference

Prometheus

Azure Monitor managed service for Prometheus + Azure Managed Grafana

First-party PaaS

Redis and Partner Databases on Azure

Prometheus & Monitoring

Vector search (cross-engine)

See the "Azure" column of the comparison below for every engine’s cloud availability

 — 

Redis and Partner Databases on Azure

Comparing Vector Databases

The decision map below groups the same options by engine family and by how much of the stack you want to manage yourself, from first-party PaaS down to self-managed on AKS/VMs:

Decision map from database engine to Azure managed option

Common concerns across every engine

The pages linked above each cover engine-specific setup and tuning; the concerns below apply, in some form, to every managed database on this list.

Networking

Every option above supports a public endpoint gated by an IP/service-tag firewall (quick to set up, fine for development) and a private endpoint — a network interface with a private IP inside your own virtual network, backed by Azure Private Link — for production traffic that should never cross the public internet. Elastic Cloud and Marketplace SaaS options (MongoDB Atlas, Redis Cloud, Couchbase Capella, Neo4j AuraDB, Qdrant Cloud) typically expose their own private-link equivalent rather than an Azure-native private endpoint; check the specific product’s networking page before assuming parity with a first-party service.

Entra ID authentication

Azure SQL Database/Managed Instance, PostgreSQL and MySQL flexible server, and Azure DocumentDB/Cosmos DB all support authenticating client connections with Entra ID identities (a user, group, or managed identity) instead of a database-local username/password, so the same role-based access review that governs the rest of a subscription also governs who can connect. Marketplace SaaS and self-managed-on-AKS options generally do not integrate with Entra ID for the data-plane connection itself — they authenticate with their own users/API keys, though Entra ID can still gate the Azure resource (the AKS cluster, the Marketplace resource) that fronts them.

Backups and point-in-time restore (PITR)

First-party PaaS options take automatic backups on a retention window you configure and support restoring to a new instance at an arbitrary point in time within it (PITR). Self-managed engines on AKS/VMs need their own backup tooling (a cron job driving the engine’s native dump/snapshot mechanism, or an operator’s built-in backup CRD) — there is no PITR for free.

HA and zone redundancy

Zone-redundant HA (synchronous replicas across three availability zones, automatic failover) is available as a tier or an add-on flag on Azure SQL Database/Managed Instance, PostgreSQL/MySQL flexible server, and Azure DocumentDB/Cosmos DB. On AKS, the equivalent is spreading an engine’s own replica set or cluster nodes across zones with pod anti-affinity and a zonal node pool — the platform gives you the zones, the engine’s own clustering does the rest.

Read replicas and geo-replication

Azure SQL, PostgreSQL/MySQL flexible server and Azure DocumentDB/Cosmos DB all support cross-region read replicas for read scaling and disaster recovery; Redis (Managed Redis and Cache for Redis) supports active geo-replication for multi-region active-active workloads. Cross-engine, this is the same replication concept covered in depth on each engine’s own reference page under this site’s Database Development section.

Scaling

First-party PaaS options scale compute (vCores) and storage independently and mostly online, with flexible server and Azure SQL both offering a serverless/auto-pause tier for spiky or dev/test workloads. On AKS, scaling means resizing the node pool and the engine’s own StatefulSet/operator-managed replica count — see AKS Clusters for the cluster-level mechanics.

Maintenance windows

PaaS options apply platform patching and minor-version upgrades inside a maintenance window you can schedule (a day-of-week/time-of-day pair) so that patching does not land during peak traffic; a self-managed AKS deployment is your own responsibility to patch, on your own schedule.

Connection strings in Key Vault

Whichever option you pick, application code should read its connection string/credentials from Key Vault rather than from a config file or an environment variable checked into source control — see Key Vault and Secrets for storing and rotating the secret itself, and Identity and Access for granting the application’s managed identity read access to it.

Migrating an existing database to Azure

Azure Database Migration Service (DMS) classic — the original standalone migration service reachable from the Azure portal — is being retired for SQL Server-to-Azure-SQL scenarios; Microsoft’s current guidance is to use the newer Azure SQL Migration tooling instead, either through the Azure portal’s own migration experience or through Azure Data Studio’s SQL migration extension where that tooling is still supported in your environment. Because Azure Data Studio itself is being retired, new migration work should start from the portal-based flow or from Visual Studio Code’s MSSQL extension rather than from Azure Data Studio. DMS classic for non-SQL-Server engines (MySQL, PostgreSQL, MongoDB) is unaffected by this specific retirement and remains a supported path for those engines' assessment-and-migrate scenarios.

A typical assessment-then-migrate flow, regardless of which tooling fronts it, looks like:

export RG=rg-bookshelf
export SUBSCRIPTION=<subscription-id>

# 1. Assess the source database for compatibility issues before migrating anything
#    (Data Migration Assistant for SQL Server, or the target service's own assessment
#    tooling for PostgreSQL/MySQL/MongoDB).

# 2. Register the Microsoft.DataMigration resource provider once per subscription.
az provider register --namespace Microsoft.DataMigration --subscription "$SUBSCRIPTION"

# 3. Run the migration itself through the current recommended tool for the target engine
#    (the Azure SQL Migration flow in the portal for SQL Server -> Azure SQL; the target
#    flexible server's own import/restore tooling for PostgreSQL/MySQL; mongodump/mongorestore
#    or the target's native import for MongoDB/DocumentDB).

Because the recommended tooling differs by target engine and changes faster than this page can track, verify the current migration path for your specific source/target pair against the Azure Database Migration Service overview before planning a cutover.