The Young DBA

Microsoft Azure Stream Analytics is a serverless scalable complex event processing engine by Microsoft that enables users to develop and run real-time analytics on multiple streams of data from sources such as devices, sensors, web sites, social media, and other applications (wiki). 10 Facts Stream Analytics is an event processing engine, which can ingest & analyze in real-time. ASA can stream data from devices, sensors, websites, social media feeds, applications, and more. Stream Analytics don't mandatory to store data, analyse data in motion as well as stored. Stream Analytics is built on a pull-based communication mode. Stream Analytics supports two input types, stream data and reference data. It has two source types, Azure Event Hubs and Azure Blob storage. Process starts with a source of streaming data that is ingested into Azure Event Hub or Azure Blob Storage. We can create a job that specifies the input source that streams data. The job also specifies a tran

For a moment if you look 15 years back to see the development of Database, Datawarehouse, and Business Intelligence. Then you will see a lot of features came and depreciated from database engines. Today I will talk about one of best feature, that grows the data warehouse "Materialized view" or "Indexed view". This is the heart of traditional data warehouse system which gives the optimized reporting and analytics. Oracle first introduced with 8i, later, Microsoft SQL Server brings in 2000 version. SQL Server's Index view is better than other RDBMS. Indexed view of SQL server is Fully optimized for Datawarehouse queries and autorefresh of data and with schema bindings. This was also the reason, so Microsoft SQL Server gets popularity in Datawarehouse Market. Postgres requires Refresh Materialized View for updated data in reports. And if you ask with MySQL developer, they will say materialized view is nothing but a logically insert into the base table and then i

Hello Friends, Continuing my learning and sharing the concept with social media, I have planned something new this year. I will explore Cloud Database and Analytics platform and will write on "YoungDBA" platform. So I have decided to write a new chain of blogs "10 Facts About". This will mainly relate to Cloud Database and Analytics Platform. I will consider Azure at the start and later will add Aws too. 10 facts will contain, 10 important basic information related to any service provided by cloud data platform provider. This is my first post on "10 Facts About". Every week I will choose a service and will share 10 facts about that like I will start with stream analytics, "10 facts about Azure Stream Analytics".  

Azure DB for MySQL released in the year 2017, this given the new advantages for those customers whose environment is SQL Server along with open source RDBMS. Now cloud database platform changes the technology parameter cutting-edge technology to bleeding edge technology, everything is being crossed platform. Recently one of the clients has thinking to shift their in-house MySQL to Azure environment. Their 70% database platform is on SQL Server and rest are on MySQL and MongoDB. We got chance to migrate existing database to Azure. The application was 3 years old and database was mix of the plug gable engine of  on tables like MyISAM, InnoDB, and csv. Like all other Azure services  MySQL  on AzureDB is also easy to setup in few clicks. We did the same but when we started migrating database, it raised the error " Azure doesn't support MyISAM ".  Actually, Azure did good for Database point of view but for existing system we required to do some changes. We changes the tab