Big Data: solutions are implemented faster, at lower cost, and less risk on Oracle than via any DIY Hadoop solution. Oracle provides the best foundation for the Internet of Things and big data analytics. Oracle unified architecture provides end-to-end data liquidity, tailored scalability, and security and privacy from the inside out. Oracle can combine data in data warehouses with big data and enable users to easily discover the value in all of their data.
Business Intelligence: provides the complete spectrum of intelligent query and analysis capabilities. It includes interactive dashboards, proactive intelligence and alerts, enterprise reporting, real-time predictive intelligence, and mobile analytics. Insight comes from any data source, Oracle and non-Oracle and extends to a broad range of executive and technical users.
Scorecard and Strategy Management: enables organizations to define strategic goals and objectives that can be cascaded to every level of the enterprise. Tracking the right Key Performance Indicators (KPIs) in their dashboards and using scorecards to measure the outcome of their actions, employees can understand their impact on achieving success and align their actions accordingly.
Hyperion Essbase: provides a real-time analytic infrastructure for insightful business intelligence and enterprise performance management (EPM) applications. At its core, Essbase contains a high performance OLAP engine with over 350 functions ranging from financial calculations to cross-dimensional clustering.
Endeca Information Discovery: is an enterprise data discovery platform for advanced, yet intuitive, analysis and exploration of complex and varied data. Fusing and augmenting diverse sources of information, Endeca Integrator offers ETL tooling for enterprise data, a Web Services API to leverage data integration tools such as Oracle Data Integrator, third party ETL, and Hadoop, and a web acquisition toolkit for gathering content from file systems, content management systems and websites.

Big Data Connectors

Oracle Big Data Connectors deliver fast data integration to enable enterprises to combine the pre-processing of large data volumes of raw and unstructured data in Hadoop with the advanced analytics, complex data management, and real-time query capabilities of Oracle Database. The components of this software suite are:
  • Oracle Loader for Hadoop uses MapReduce to format and load data efficiently into Oracle Database.
  • Oracle SQL Connector for HDFS enables Oracle Database to seamlessly query or load data from HDFS via external tables using SQL.
  • Oracle Data Integrator Application Adapter for Hadoop generates optimized MapReduce and data loading routines via a graphical interface and specific ODI Knowledge Modules. The modules also support Hive, HDFS, HBase, OLH/OSCH, and Sqoop.
  • Oracle R Advanced Analytics for Hadoop enables the open-source statistical environment R to run in parallel across Hadoop clusters for scalable analytics of data.
  • Oracle XQuery for Hadoop enables XQuery to run natively across a Hadoop Cluster so that it can process and transform text, XML, JSON, and Avro content stored in a HDFS, Hive or Oracle NoSQL Database.


GoldenGate for Big Data

GoldenGate for Big Data enables real-time big data analytics by streaming transactional data from a variety of heterogeneous systems into big data systems such as Hadoop, HDFS, HBase, Hive, Flume, Oracle NoSQL, and others. Keeping big data reservoirs or lakes up to date raises the timeliness of business insights.


Big Data Discovery

Big Data Discovery, the visual face of Hadoop, is an interactive and easy to use product, built natively on Hadoop to transform raw data into business insight in minutes, without the need to learn complex products or rely only on highly skilled resources. Machine-learning algorithms are then applied behind the scenes to surface interesting correlations and patterns and offer suggested visualizations for exploring attributes. Analysts can intuitively explore a rich catalog of all the raw data in a Hadoop cluster, sort by information potential, experiment with different combinations of data, assess attribute statistics and data quality, leverage an extensive library of data transformations and enrichments, and share data set summaries and annotations.


Big Data Spatial and Graph

Big Data Spatial and Graph runs on Hadoop and NoSQL technologies to bring graph, spatial and raster data processing to the Big Data platform. It provides a wide range of spatial analysis functions and services to evaluate data based on how near or far something is to one another, whether something falls within a boundary or region, or to process and visualize geospatial map data and imagery. In addition, it includes a property graph database and 35 built-in graph analytics that discover relationships, recommendations and other graph patterns in big data.


Big Data SQL

Big Data SQL combines distributed data from Oracle Database, Hadoop and NoSQL in a single, optimized SQL query. Via automatically generated Oracle Database external tables, organizations can use the SQL skills they already have to query data in Hadoop and NoSQL and to integrate big data analysis into existing applications and architectures. Moreover, Big Data SQL extends security and access policies from Oracle Database to data in Hadoop and NoSQL. It also enables Smart Scan and local storage processing on all data to maximize query performance and minimize data movement.


NoSQL Database

Oracle NoSQL Database is a distributed, enterprise class key value store for large volume data, latency sensitive applications, or big data processing. It scales horizontally to hundreds of nodes with high availability and transparent load balancing via an intelligent driver which keeps track of the underlying storage topology and shards the data. It features easy administration, a simple programming model, and adjustable durability and consistency transactional guarantees.


Data Integrator Enterprise Edition Big Data Option

Data Integrator Enterprise Edition Big Data Option increases developer productivity by solving the most complex and time sensitive Big Data transformation and movement challenges. Decoupling the logical design and physical implementation, it lets customers choose between multiple Big Data technologies that best meets their requirements and leverages their cluster capabilities. Customers can select between Hive, Spark, and Pig as the native generated transformation language, as well as between the traditional ODI Agent or Apache Oozie as the job orchestration/scheduling engine.



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