In almost every organization, SQL is at the heart of enterprise data used in transactional systems, data warehouses, columnar databases and analytics platforms to name just a few examples. Additionally, a vast number of commercial and in-house developed tools used to access, manipulate and visualize data rely on SQL. SQL is lifeblood of the modern transaction and decision support systems.
An organization’s readiness for Hadoop is not a single state held by a single entity. Corporations, government agencies, educational institutions, healthcare providers, and other types of organizations are complex in that they have multiple departments, lines of business, and teams for various business and technology functions. Each function can be at a different state of readiness for Hadoop, and each function can affect the success or failure of Hadoop programs.
Presto addresses a real need for a portable SQL on Hadoop tool. It is architected from the ground up for high performance interactive query processing. Open source is a fount of continual innovation, especially with regard to big data. In addition, there are strong tools that come with specific Hadoop distributions. The fact is that organizations will deploy multiple tools. For organizations moving toward a Unified Data Architecture, the rationale for adopting Presto is even stronger.
A White paper by Philip Howard, Bloor Research International Ltd on critical considerations for Hadoop deployments and the role of appliances.
I recently caught up with Ravi Mayuram, SVP Products & Engineering at Couchbase, to discuss recent developments in the NoSQL database industry such as the relationship with Hadoop and Spark, container technology, security, and much more.
In their efforts to extract value from big data, organizations around the world are turning to the Hadoop big data collection, management and analysis platform. Hadoop offers two important services: store any kind of data from any source, inexpensively and at very large scale, and perform sophisticated analysis of that data easily and quickly. To learn more about Hadoop and big data download this white paper.
Welcome to Hadoop For Dummies! Today, organizations in every industry are being showered with imposing quantities of new information. Along with traditional
sources, many more data channels and categories now exist. To learn more about Hadoop download this guide.
Reporting and analysis drives businesses in making the best possible decisions. The source of all these decisions is the data. We explain the top 5 challenged for Hadoop MapReduce in the enterprise. Learn more by downloading this white paper.
Hadoop is an open-source software framework for storage and processing of large data sets on clusters of inexpensive hardware. Hadoop was created by Doug Cutting and Mike Cafarella and adopted by Apache, and is supported by a global community of contributors and users. Part of Hadoop’s appeal is that it offers a means of storing and processing very large amounts of data more cost-effectively than traditional databases or data warehouses. Learn more by downloading this white paper.
Hadoop: Moving Beyond the Big Data Hype – let’s face it. There is a lot of hype surrounding Big Data and Hadoop, the de facto Big Data technology platform. Download this guide to learn more.