As companies continue to implement and use Hadoop to analyze large-scale data, Hadoop software partnerships refine their products for use in business, and strive to respond to specific concerns such as reliability and scale. This is especially true as the newest trend towards the Internet of Things come to bear on the market.

With the integration of bigger infrastructure and high data flow that entails, Big Data is one of the guidelines in vogue for IT in the coming years. Splunk has developed an engine that enables the capture and evaluation of large amounts of big data in real time. Real-time data can be monitored, analyzed, and display with terabytes of historical data, both on-premise and in the cloud.

Hadoop promises low cost and high scalability in terms of quantity and flexibility in the structure of the data. Splunk, which collects, indexes and harnesses the machine-generated big data coming from the websites, applications, servers, networks and mobile devices, has recently made a number of strategic alliances with leading vendors to monitor, search, analyze, visualize and act on massive streams of real-time and historical machine data.

Splunk and Cloudera partner to accelerate Hadoop data

Cloudera and Splunk are joining in a strategic alliance that will see their respective enterprise platforms linked via the Splunk Hadoop Connect tool.

The Splunk Enterprise platform collects machine data from wherever it’s generated in real time including Websites, mobile devices, servers, and lots of other infrastructure. The platform is useful for monitoring end-to-end infrastructure, or even customer behavior. The Splunk Hadoop Connect feature of Enterprise platform moves data between Splunk Enterprise and the Apache Hadoop framework.

Under the terms of the alliance, Splunk will integrate Splunk Hadoop Connect with Cloudera’s open-source Hadoop software package to deliver data to Hadoop, or ingest data into Splunk from Hadoop, such as the output of Hadoop MapReduce jobs and easily analyze and visualize that data. Splunk Hadoop Connect seamlessly integrates with Cloudera CDH4.2 enabling data from Splunk to be reliably sent to Cloudera for specialized batch analytics that power many features.

For Splunk, the alliance with Cloudera offers it more distribution for its visualization and search tools.

Splunk, Hortonworks Team for Big Data BI

Hadoop innovator Hortonworks and Splunk are tackling interoperability between their respective platforms to enable companies with the use of the open source Apache Hadoop solution with Splunk Hadoop Connect.

Hortonworks, which recently introduced Microsoft Windows Server support, is integrating Hortonworks Data Platform (HDP) and Splunk Hadoop Connect to collect machine data from across the organization and deliver it to Hadoop for batch analytics. Likewise, the output of Hadoop jobs can be imported into Splunk Enterprise for rapid analysis and visualization.

HDP is the only 100-percent open source data management platform for Apache Hadoop and HDP for Windows not only enables organizations to deploy Hadoop projects on Windows Server but also allows for easy migration to Windows Azure HDInsight Service in the cloud.

The alliance with Splunk will help extend the Apache Hadoop ecosystem and further drive open source community innovation for the next-generation enterprise data platform.

Splunk for AWS

A whole host of IT companies set out to analyze the data stored and cloud adoption is a strategy for IT organizations to increase elasticity and decrease time to market. Splunk is geared to provide the analysis of machine-generated big data via the leading cloud provider – Amazon Web Services (AWS).

Splunk launched Splunk Storm, which is aimed at companies who develop their applications in the public cloud and provide for infrastructure services such as AWS, Heroku, Google App Engine or Rackspace. Splunk Storm is a fully managed multi-tenant service on AWS that includes all resources for data storage and analysis.

With Storm, users can index and store special parser or connectors machine data regardless of source, format, platform and cloud providers; users can use the Splunk search language to search real-time and historical machine data, to filter events, to link information in different formats and transactions across multiple application components across each other and track important operating parameters; users can gain from their machine data exactly the information they need and use it to create dynamic and iterative reports; and users can give their colleagues an insight into their projects in order to achieve a cross-functional transparency of data.

Big Data Analytics with DataSift

Splunk has another strategic partnership with DataSift, a social data software startup, which integrates Splunk’s log management and analytic systems with DataSift’s real-time social media feeds. DataSift will use Splunk Storm Cloud, Splunk Enterprise or a mixed environment to collect and run analytics on terabytes of social data within minutes.

The speed and ease-of-use of Splunk software combined with the power of DataSift’s social data platform gives users the ability to immediately know when operational issues impact the brand and by how much. In addition, companies can develop a plan of action based on hard data and begin analyzing operational and social data together in the cloud without the need for servers, system administrators, Hadoop clusters or BI experts.

Splunk in Analytics Delivery Framework

Companies rarely get the real benefits of ownership of large amounts of data. Existing BI and DW tools for analysis, management and monitoring are not designed to handle large volumes of dynamically changing unstructured information. Splunk is designed a single versatile means for processing the total data generated by IT systems based on the collection, indexing and storage of these data as a sequence of events, provided with a timestamp.

Saxon Global Inc., a business intelligence and big data solutions provider, recently signed a partnership agreement with Splunk to make Saxon’s machine data accessible across an organization and identifies data patterns, provides metrics, diagnoses problems, and provides intelligence for business operations.