Build a Modern Data Architecture
The shift to data-oriented business is happening. These data-oriented businesses have created an entirely new class of storage and processing needs. Sensors, social media, web logs—all produce data that grows exponentially and without structure. Dismissed as fumes, this data was considered too expensive to store, extract, and analyze. Until now.
Hortonworks Data Platform (HDP) helps your enterprise deliver that set of capabilities by integrating Apache Hadoop into your modern data architecture. This enables you to capture, store and process vast quantities of data in a cost efficient and scalable manner, unleashing analytic opportunities and innovations.
Achieve Instant Insight and Infinite Scale with SAP HANA and Hortonworks Data Platform
- How Hadoop and SAP HANA are complementary technologies in the modern data architecture.
- How a data reservoir with Hadoop will deliver organizations the ability to gain deep insight.
- How SAP HANA, SAP Business Objects BI, SAP InfiniteInsight , SAP IQ plus the Hortonworks Data Platform can provide you a complete Big Data solution.
The partners you rely on, rely on Hortonworks for Hadoop
At all points in the data center architecture, from ETL through to processing and analysis, Hortonworks has joined forces with key partners trusted globally to provide enterprise solutions in the data center.
Hortonworks’ Strategic Relationships
Hortonworks Data Platform runs across the broadest array of datacenter infrastructure owing to native Linux and Windows support. It is also available in integrated hardware from Teradata, and HDP provides the basis for Microsoft’s HDInsight Service meaning complete portability of data is retained on-premise and in the cloud.
The explosion of data in the enterprise has created an entirely new class of storage and processing requirements that were never envisioned when our legacy RDBMS systems first came into being. It is machine generated data, sensor data, social data, web logs and other such types that are both growing exponentially, but also often unstructured in nature. It also includes data that was once thought of as low to medium value or even ‘exhaust data’: too expensive to store and analyze. And it is this type of data that is turning the conversation from “data analytics” to “big data analytics”: because so much insight can be gleaned for business advantage.