Best Application Development Software for Azure Analysis Services

Microsoft SQL Server 2019 includes intelligence and security. You get more without paying extra, as well as best-in-class performance for your on-premises requirements. You can easily migrate to the cloud without having to change any code. Azure makes it easier to gain insights and make better predictions. You can use the technology you choose, including open-source, and Microsoft's innovations to help you develop. Integrate data into your apps easily and access a rich set cognitive services to build human-like intelligence on any data scale. AI is built into the data platform, so you can get insights faster from all of your data, both on-premises or in the cloud. To build an intelligence-driven company, combine your enterprise data with the world's data. You can build your apps anywhere with a flexible platform that offers a consistent experience across platforms.

StarfishETL is a Cloud iPaaS solution, which gives it the unique ability to connect virtually any kind of solution to any other kind of solution as long as both of those applications have an API. This gives StarfishETL customers ultimate control over their data projects, with the ability to build more unique and scalable data connections.

Full-featured IDE for coding, debugging, testing, and deployment to any platform. Code faster. Work smarter. Create the future using the best-in class IDE. From initial design to final deployment, you can develop with the entire toolkit. Improved IntelliSense performance when working with C++ files. Local development with a variety of emulators. Solution Explorer simplifies test access. The IDE now supports Git management, including repo creation. Microsoft Azure workload now includes Kubernetes. Live Share allows you to instantly share your app with your peers, regardless of the type of app, programming language, or OS you are using. You don't need to set up an environment or clone the repo to start sharing.

Integrate your data sources including relational and NoSQL database, SaaS and APIs. You can query them immediately as a single source of data. Process data wherever you are. Data from different sources can be merged, retrieved, and cached. Use webhooks for streaming data from Kafka or Segment into the Peaka Table. Real-time data access replaces nightly batch ingestion. Treat each data source as a relational database. Convert any API into a table and combine and join it with other data sources. Use familiar SQL to run queries on NoSQL databases. The same skills can be used to retrieve data from SQL and NoSQL database. You can query and filter your consolidated datasets to create new data sets. Use APIs to expose them and serve other apps or systems. Don't get bogged down with scripts and logs when setting up your data stack. Eliminate the burdens of managing and maintaining ETL pipelines.