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What I like most about Azure SQL database is its fully managed and easily scalable. It removes much of the operational burden with features like automatic backups like snapshot tracking, patching and high availability. Another advantage is its seamless integration with broader Microsoft Azure Ecosystem which makes it convenient to connect with analytics, security and data processing services.
Reliability, ease of creation and quick scaling.
The ability to scale compute resources up and down or use a serverless tier that pauses when not in use. The built-in AI that auotmaitically identifies missing indexes and fixes query plan regressions. The backup system is also great in that I can restore the database to a specific minute without managing transaction logs manually.
One main challenge is its integration with non-Azure tools which is not always seamless. While it works very well with Microsoft Azure ecosystem , connecting and managing workflows across external platforms can require additional configuration and efforts. Another area that feels behind is AI assisted capabilities, Compared to many modern data platforms that often more intuitive built in AI features for query generation, optimization and development workflows, the experience here is still evolving and not smooth or accessible.
Lacking some advanced tool that you get with on premise SQL.
The DTU vs vCore models is confusing and often difficult to predict monthly pricing. NNot having access to SQL Agent jobs, certain cross database queries or filesystem can make it difficult to migrate over legacy apps. There can also be some network latency depending on where your app is hosted.