Best Data Management Software for IBM InfoSphere Optim Data Privacy

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.

IBM Db2®, a family of hybrid data management tools, offers a complete suite AI-empowered capabilities to help you manage structured and unstructured data both on premises and in private and public clouds. Db2 is built upon an intelligent common SQL engine that allows for flexibility and scalability.

IBM Informix®, a fast and flexible database that can seamlessly integrate SQL, NoSQL/JSON and time series data, is available. Informix's versatility and ease-of-use make it a popular choice for a wide variety of environments, including enterprise data warehouses and individual application development. Informix is also well-suited for embedded data management solutions due to its small footprint and self-managing capabilities.

Apache Hadoop is a software library that allows distributed processing of large data sets across multiple computers. It uses simple programming models. It can scale from one server to thousands of machines and offer local computations and storage. Instead of relying on hardware to provide high-availability, it is designed to detect and manage failures at the application layer. This allows for highly-available services on top of a cluster computers that may be susceptible to failures.

Organizations can support their business goals by managing data well over its life span. Decommissioned applications and historical transaction records can be archived. However, you will still have access to the data for queries and reporting. You can scale data across applications, operating systems, and hardware platforms to improve security, speed up release cycles, and reduce costs. Data archiving is critical to the performance of mission-critical enterprise systems. Reduce data growth issues at the source, increase efficiency, and minimize the risks associated managing structured data throughout its life. Unstructured data can be protected in the testing, development, and analytics environments throughout an enterprise.