Big Data Database, Appliance and Big Data Connectors

Oracle’s Big Data Appliance includes Intel’s new processors and the latest release of CDH (Cloudera’s Distribution, including Apache Hadoop) and Cloudera Manager, as well as Oracle Enterprise Manager Plug-In for
Oracle Big Data Database Appliance. Oracle Big Data Connectors have been enhanced to enable greater database SQL access to Hadoop from Oracle Database.

Oracle Big Data Appliance and Connectors
Oracle Big Data Appliance

 

“An influx of raw data sets is flooding every enterprise. However, before businesses can take advantage of the potential opportunity, they face a significant challenge in organizing these diverse datasources,” says Cetin Ozbutun, vice president of data warehousing and big data technologies at Oracle. “The latest updates further improve the abilities of our customers to optimize big data workloads and integrate them with their data warehouses to easily analyze all data throughout the enterprise.”

Big Data Database: appliance and connectors

Oracle Big Data Appliance is an open, multi-purpose engineered system for Hadoop and NoSQL processing. It runs a diverse set of workloads – from Hadoop-only workloads (MapReduce 2, Spark, Hive etc.) to interactive, all-encompassing interactive SQL queries using Oracle Big Data database SQL. Big Data Appliance provides an open environment for innovation while maintaining tight integration and enterprise-level support. Organizations can deploy external software to support new functionality – such as graph analytics, natural language processing and fraud detection. Support for non-Oracle components is delivered by their respective support channels and not by Oracle.

In addition to providing Oracle Big Data database SQL and the full Cloudera software platform, Big Data Appliance utilizes Oracle Big Data Connectors to simplify data integration and analytics. Big Data Connectors provide high-speed access to data in Hadoop from Oracle Exadata and Oracle Database – with data transfer rates on the order of 15 TB/hour. Big Data Connectors also enable integrated, highly scalable analytics – providing native access to Hadoop data and parallel processing using Oracle R Distribution. Finally, Oracle XQuery for Hadoop facilitates standard XQuery operations to process and transform documents in various formats (JSON, XML, Avro and others), executing in parallel across the Hadoop cluster.

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What is the value of Big Data ?

If you are looking for instant answers on what is the value of big data, you can access Oracle’s exclusive material published on their website. Straightforward approaches for acquiring, organizing, and analyzing big data; architectures and tools needed to integrate big data with your existing investments; survey data revealing how leading companies are using big data; the value of big data and expert resources such as white papers, analyst videos, and demos.

Huge volumes of big data are generated by companies world-wide. However, usually this data is not kept around long enough for big data analysis because you don’t have the tools or techniques to exploit it.

How do you turn this data from digital exhaust into business value? Read the comprehensive e-book to get advice from Oracle and industry leaders on how you can use big data to generate new business insights and make better decisions. You’ll gain access to:
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Big Data for the Enterprise (White paper)

Today the term big data draws a lot of attention, but behind the hype there’s a simple story. For decades, companies have been making business decisions based on transactional data stored in relational databases. Beyond that critical data, however, is a potential treasure trove of non-traditional, less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Decreases in the cost of both storage and compute power have made it feasible to collect this data – which would have been thrown away only a few years ago. As a result, more and more companies are looking to include non-traditional yet potentially very valuable data with their traditional enterprise data in their business intelligence analysis.

To derive real business value from big data, you need the right tools to capture and organize a wide variety of data types from different sources, and to be able to easily analyze it within the context of all your enterprise data. Oracle offers the broadest and most integrated portfolio of products to help you acquire and organize these diverse data types and analyze them alongside your existing data to find new insights and capitalize
on hidden relationships.

Big data typically refers to the following types of data:

  • Traditional enterprise data – includes customer information from CRM systems, transactional ERP data, web store transactions, general ledger data.
  • Machine-generated /sensor data – includes Call Detail Records (“CDR”), weblogs, smart meters, manufacturing sensors, equipment logs (often referred to as digital exhaust), trading systems data.
  • Social data – includes customer feedback streams, micro-blogging sites like Twitter, social media platforms like Facebook

Big data Growth
The McKinsey Global Institute estimates that data volume is growing 40% per year, and will grow 44x between 2009 and 2020.

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Report: Cost/Benefit of Enterprise Warehouse Solutions

In-depth Comparison of IBM Smart Analytics System 7700,
Teradata Active Enterprise Data Warehouse and
Oracle Exadata Database Machine.

Data warehousing has emerged as one of the IT world’s fastest growth areas. New deployments continue to accelerate, and numbers of applications and users within organizations continue to expand. Demand for high-quality, current information and for tools to interpret and exploit it shows no signs of abating. High
double-digit growth in data volumes has become the norm.

The business benefits of data warehouse applications are clearly recognized. But, increasingly, users are faced with escalating expenditure not only on data warehouse solutions, but also on underlying platforms. At a time of budgetary pressures, questions are raised about the most cost-effective means of realizing
information value.

This is particularly the case for special-purpose platforms offered by IBM (Smart Analytics System, Netezza TwinFin), Oracle (Exadata Database Machine), Teradata (Active Enterprise Data Warehouse) and smaller players. Architectures and technologies of these systems are often unfamiliar to organizations that deploy them. Techniques for measuring comparative performance and cost are rudimentary.

Challenges are compounded by several factors. One is that the performance of different architectures depends on the workloads they execute. Another is that data warehouse usage tends to evolve rapidly – organizations that deploy platforms for specific applications may soon find that they must deal with significantly different environments. A third is that vendor pricing may vary widely between customers.

This report sets some parameters for comparisons. To do this, it takes into account types of workload – in particular, a key distinction is drawn between complex mixed workloads and queries involving large sequential table scans – compares overall three-year as well as acquisition costs, and bases platform calculation on “street” pricing (i.e., discounted prices paid by users).

The report focuses on three platforms: IBM Smart Analytics System 7700, Oracle Exadata Database Machine and Teradata’s flagship Active Enterprise Data Warehouse (Active EDW) 6650. Results are based on input from 46 users of these systems and their recent predecessors, on other industry sources, as well as on research and analysis conducted by the International Technology Group (ITG).

Two sets of cost comparisons, based on performance and user data, are presented.

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Oracle Big Data Appliance

The creation of data has always been part of the impact of information and communications technology. As the amount of data available for analysis continues to grow, the challenge is for organizations to find the technology that would give them the ability to disseminate, understand and ultimately benefit from the increasing volumes of data. Oracle has recently announced the release of what they consider a viable solution to handle the challenge of Big data. The Oracle Big Data Appliance consists of optimized hardware and several software products from Oracle Corporation .The Oracle Big Data Appliance in union with Oracle Exadata Database Machine and the Oracle Exalytics Business Intelligence Machine (Oracle Exalogic) is used for obtaining, consolidating and loading unstructured data into the Oracle Database 11g. The solution consists of an open source distribution of Apache Hadoop, Oracle NoSQL Database, Oracle Data Integrator with Application Adapter for Hadoop, Oracle Loader for Hadoop, an open source distribution of R, Oracle Linux, and Oracle Java Hotspot Virtual Machine.

Oracle announced the Oracle Big Data Appliance Mon, October 3 at Oracle OpenWorld 2011.

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