Data Warehouse Engines handle storage, querying and load mechanisms of large database. It is an indisputable fact that implementing a data warehouse is such a very challenging task. This becomes even more challenging and difficult to do when we take into consideration the diversity of both operational data sources and target data warehouse engines.
Data warehouse engines vary depending on the needs of the organization. But it is common today to acquire data warehouse engines that can handle the needs of very big, terabyte-scale business intelligence applications. This will make organizations get faster information to help then achieve success in the competition.
The foundation of a modern data warehousing architecture is the Hybrid Data Warehouse or Logical Data Warehouse (LDW). A Hybrid Data Warehouse, is comprised of multiple data warehousing technologies and platforms so that the right workload is running on the right technology. From Hadoop to on-premises analytical engines to cloud-based data stores, the LDW helps you support proactive decision making, reduce costs, streamline processes, and increase business user agility.
No-boundaries database software for the digital, cloud and cognitive era
IBM® DB2® is the database of choice for enterprise-wide solutions. Optimized to deliver industry-leading performance while lowering costs, IBM DB2 offers extreme performance, flexibility, scalability and reliability for any size organization.
A fully managed cloud or local data warehouse, purpose-built for analytics. It offers MPP scale and seamless compatibility with a wide range of business intelligence tools
dashDB is next-generation data warehousing and analytics technology for use in private clouds, virtual private clouds and other container-supported infrastructures. It is ideal when you must maintain control over data and applications, yet want cloud-like simplicity. dashDB Local is part of a family that shares a common SQL engine and other database technologies across different deployments so you can place the right workload on the right platform—and move between them without application change. It includes in-memory processing for delivering insanely fast answers to queries, as well as MPP for scale out and scale up capabilities as data grows. It also provides scale-in capabilities to free resources after peak workloads complete. For analytics, leverage familiar SQL, R predictive modeling or robust Netezza analytics, including geospatial support.
Meeting big data challenges with simplicity, speed and lower cost
IBM® PureData™ for Analytics, powered by Netezza technology, is changing the game for data warehouse appliances.
Codified data management best practices are provided for each workload. PureData System delivers automated pattern-based deployment and management of highly reliable and scalable database services.
Integration by design
Hardware, storage and software capabilities are designed and optimized for specific high performance data workloads such as patented data filtering using programmable hardware (FPGAs) for ultrafast execution of analytic queries without the need for indices.
The PureData System provides single part procurement with no assembly required (ready to load data in hours), open integration with 3rd party software, and integrated management console for the entire system, single line of support, integrated system upgrades and maintenance.
Big Data and Business Intelligence ready
In addition to the features and benefits of the data warehouse appliance itself, you now get the added benefit of additional software to exploit big data opportunities and leading business intelligence capabilities. Included with the data warehouse appliance are software licenses to get you started with IBM Cognos for business intelligence, IBM InfoSphere DataStage for data integration, IBM BigInsights to augment your data warehouse with Hadoop data services and IBM InfoSphere Streams for an introduction to real-time streaming analytics.
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