Oracle Machine Learning Integrations

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.

MySQL is the most widely used open-source database in the world. MySQL is the most popular open source database for web-based applications. It has been proven to be reliable, performant, and easy-to-use. This database is used by many high-profile web properties, including Facebook, Twitter and YouTube. It is also a popular choice for embedded databases, distributed by thousands ISVs and OEMs.

Connect your product to hotel data within minutes. Securely read and write to multiple hotel systems with one powerful, well-documented JSON interface. Connect your app to our Test Hotel in minutes. Real hotels can be connected in days, not weeks. All you need to connect to multiple hotel systems is one easy-to-understand REST API. Impala is bank-grade secure, GDPR-compliant, and uses geographically diverse hosting. Impala will be your last PMS integration. We connect your app to hotel data through a growing number property management systems. We are constantly adding hotel systems so that you can sell to a wider variety of hotels each month. Modern hotel technology requires complete data. Impala provides that seamlessly and in both directions. The Impala API offers a wide range of data, including guest information, transaction details, and updates on rate changes.

A cloud database that can scale to handle large streaming data sets. Kinetica harnesses modern vectorized processors to perform orders of magnitude faster for real-time spatial or temporal workloads. In real-time, track and gain intelligence from billions upon billions of moving objects. Vectorization unlocks new levels in performance for analytics on spatial or time series data at large scale. You can query and ingest simultaneously to take action on real-time events. Kinetica's lockless architecture allows for distributed ingestion, which means data is always available to be accessed as soon as it arrives. Vectorized processing allows you to do more with fewer resources. More power means simpler data structures which can be stored more efficiently, which in turn allows you to spend less time engineering your data. Vectorized processing allows for incredibly fast analytics and detailed visualizations of moving objects at large scale.

Oracle database products offer customers cost-optimized, high-performance versions Oracle Database, the world's most popular converged, multi-model database management software. They also include in-memory NoSQL and MySQL databases. Oracle Autonomous Database is available on-premises via Oracle Cloud@Customer and in the Oracle Cloud Infrastructure. It allows customers to simplify relational databases environments and reduce management burdens. Oracle Autonomous Database reduces the complexity of operating and protecting Oracle Database, while delivering the highest levels performance, scalability and availability to customers. Oracle Database can also be deployed on-premises if customers have network latency and data residency concerns. Customers who depend on Oracle database versions for their applications have full control over which versions they use and when they change.

Oracle Cloud Infrastructure supports traditional workloads while delivering modern cloud development tools. It's designed to protect against modern threats so that you can invent more. To lower your TCO, combine low cost and high performance. Oracle Cloud is a Generation 2 enterprise-class cloud that delivers powerful compute, networking, and includes a wide range of infrastructure and platform cloud services. Oracle Cloud was built from the ground up to support legacy workloads and deliver modern cloud development tools. This allows enterprises to bring their past forward while building their future. Our Generation 2 Cloud is the only one that can run Oracle Autonomous Database, which is the first and only industry-leading self-driving database. Oracle Cloud offers a complete cloud computing portfolio that includes application development, business analytics, data management, integration, security, and blockchain.

Check-In is a platform that combines two products. It was designed with privacy in mind. Status Connect connects you to your people. It allows them to quickly report changes in work conditions and verify their health status. This helps you identify potential risks. Employers can help their employees feel safer by using Automatic Contact Tracing to identify their risk of exposure so that leaders can quickly communicate any potential exposure to their staff. Businesses that have started to return employees to the workplace will build trust and confidence with their workforce. Leaders will be able to quickly connect and learn about the current health status of their workforce and any productivity issues. You can get the information you need in order to make critical decisions, keep your employees safe, reduce risks for your business, and increase confidence about returning to work.

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.