Best Data Management Software for IBM API Connect

Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.

Apache Hive™, a data warehouse software, facilitates the reading, writing and management of large datasets that are stored in distributed storage using SQL. Structure can be projected onto existing data. Hive provides a command line tool and a JDBC driver to allow users to connect to it. Apache Hive is an Apache Software Foundation open-source project. It was previously a subproject to Apache® Hadoop®, but it has now become a top-level project. We encourage you to read about the project and share your knowledge. To execute traditional SQL queries, you must use the MapReduce Java API. Hive provides the SQL abstraction needed to integrate SQL-like query (HiveQL), into the underlying Java. This is in addition to the Java API that implements queries.

iDashboards helps you move beyond the burden of spreadsheets and blend data from multiple sources into dynamic, custom dashboards.

Streamline the classification, recognition, and capture of business documents. IBM® Datacap software forms a key capability in the IBM Cloud Pak®. This is for Business Automation. It simplifies the classification, recognition, and capture of business documents. It uses text analytics, natural language processing, and machine learning to extract content from unstructured and variable paper documents. Multichannel input from scanners and faxes, emails and digital files, such as PDF and images from mobile devices and applications. Machine learning is used to automate complex or unidentified formats and highly variable documents that are difficult to capture using traditional systems. Allows you to export information and documents to a variety of applications and content repositories, including IBM and other vendors. To speed up deployment, this interface allows you to configure capture workflows and apps with a simple point-and click interface.