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Hadoop

The Apache Hadoop framework for the processing of data on commodity hardware is at the center of the Big Data picture today. Key solutions and technologies include the Hadoop Distributed File System (HDFS), YARN, MapReduce, Pig, Hive, Security, as well as a growing spectrum of solutions that support Business Intelligence (BI) and Analytics.



Hadoop Articles

Snowflake Computing, a provider of cloud data warehouse technology, is extending its concept of the modern data warehouse to what it calls a "data sharehouse."

Posted June 22, 2017

SAP and Accenture are expanding their collaboration to co-innovate, co-develop, and jointly go to market with digital solutions based on the new SAP Leonardo digital innovation system. The long-standing strategic partners will focus on embedding digital technologies including additional machine learning, analytics, and the Internet of Things (IoT) at the core of clients' businesses to deliver even greater value from their SAP investments.

Posted June 21, 2017

Syncsort, a provider of data integrity and integration solutions for next-generation analytics, has announced new capabilities in its mainframe data access and integration solution that populates Hadoop data lakes with changes in mainframe data.

Posted June 20, 2017

New and emerging vendors offer fresh ways of dealing with data management and analytics challenges. Here, DBTA looks at the 10 companies whose approaches we think are worth watching.

Posted June 16, 2017

A new era of computing is unfolding with big data, cloud, and cognitive all converging at once. This confluence will transform how we do business and it's impacting all industries.

Posted June 16, 2017

The world of data management is constantly changing. Each year, the DBTA 100 spotlights the companies that are dealing with evolving market demands through innovation in software, services, and hardware.

Posted June 15, 2017

IBM and Hortonworks are expanding their partnership focused on extending data science and machine learning to more developers and across the Apache Hadoop ecosystem. The companies are combining the Hortonworks Data Platform (HDP) with the IBM Data Science Experience and IBM Big SQL into new integrated solutions designed to help users better analyze and manage data for better decision making.

Posted June 13, 2017

Attunity Ltd., a provider of data integration and big data management software solutions, is launching a new solution, Attunity Compose for Hive, which automates the process of creation and continuous loading of operational and historical data stores in a data lake.

Posted June 13, 2017

Addressing the rise of hybrid deployments, Hortonworks has introduced a new software support subscription to provide seamless support to organizations as they transition from on-premise to cloud. Separately, Hortonworks also announced the general availability of Hortonworks Dataflow (HDF) 3.0, a new release of its open source data-in-motion platform, which enables customers to collect, curate, analyze and act on all data in real-time, across the data center and cloud.

Posted June 12, 2017

Hadoop adoption is growing and so is the commitment to data lake strategies. Data security, governance, integration, and access have all been identified as critical success factors for data lake deployments.

Posted June 09, 2017

The demand for speed and agility are among the key drivers of the growing DevOps movement, which seeks to better align software development and IT operations. Yet, challenges still exist.

Posted June 07, 2017

Databricks has introduced a new offering to simplify the management of Apache Spark workloads in the cloud. "Databricks Serverless" is a managed computing platform for Apache Spark that allows teams to share a pool of computing resources and automatically isolates users and manages costs. The new offering aims to remove the complexity and cost of users managing their own Spark clusters.

Posted June 06, 2017

MapR Technologies, Inc., provider of a converged data platform that integrates analytics with operational processes in real time, has announced MapR-XD, a cloud-scale data store to manage files and containers. As part of the MapR Converged Data Platform, MapR-XD supports any data type from the edge to the data center and multiple cloud environments with automatic policy-driven tiering from hot, warm or cold data to enable customers to create global data fabrics which are ready for analytical and operational applications.

Posted June 06, 2017

In the last few years, a frequent topic of conversation within some of the largest corporations in the world has been the move to the cloud—how to prepare for it, how to address it, and how to benefit from it. Yet over the past several months, some are also talking about a more ambitious goal: to be cloud-only by 2025.

Posted June 01, 2017

Pythian, a technology services provider, is launching a customized analytics solution that integrates multiple data types from both internal and external sources. The new solution, "Kick Analytics As A Service" (Kick AaaS), gathers multi-source, multi-format data together in the cloud, and adds advanced analytics, machine learning and visualizations to ensure business users and business systems get the insights they need when they need them

Posted May 31, 2017

Qubole, the big data-as-a-service company , is building an autonomous data platform that will include Qubole Data Service (QDS) Community Edition, QDS Enterprise Edition, and QDS Cloud Agents. The solution can intelligently automate and analyze platform usage to make data teams more effective.

Posted May 26, 2017

It's imperative businesses plan strategically ahead for the future. Combine that with the myriad of choices a database professional or arcitecht has when it comes to future proofing their business. Mike King, enterprise technologist of big data at Dell EMC, covered a variety of databases, unique advantages and disadvantages of each, usage, tidbits, strategy, and more during his presentation titled "Crafting Your Database Strategy for the Future" at Data Summit 2017.

Posted May 26, 2017

Data Summit 2017 was recently held in NYC. New big data technologies, cloud, and analytics were among the key areas scrutinized in educational presentations, keynotes, and hands-on workshops.

Posted May 24, 2017

Enterprises are always looking to improve their business intelligence strategies. Hadoop is one tool that can successfully support the onboarding of business intelligence workloads. Josh Klahr, vice president of AtScale, addressed the "Do's and Don'ts for Success with BI on Big Data" during his session at Data Summit 2017.

Posted May 17, 2017

The second day of Data Summit 2017 began by focusing on the current state of big data analytics as it meets information governance.The keynote was presented by Linda G. Sharp, associate general counsel at ZL Technologies, and Bennett B. Borden, chief data scientist at Drinker Biddle & Reath.

Posted May 17, 2017

Big data isn't notable because there is a lot of data that can now be stored and processed more cost-effectively. It is important because of what can be done with it. One approach that has been heralded for gaining more value from big data is the data lake, noted Jonathan Gray, CEO and founder of Cask in a presentation titled, "Building an Enteprise Data Lake," at Data Summit 2017, taking place at the New York Hilton Midtown, May 16-17, 2017.

Posted May 16, 2017

Streaming data was explored from two perspectives in a session, titled "The Streaming Future of Big Data," as part of the Hadoop Day Track at Data Summit 2017.

Posted May 16, 2017

When people talk about the next generation of applications or infrastructure, what is often echoed throughout the industry is the cloud. On the application side, the concept of "serverless" is becoming less of a pipe dream and more of a reality. The infrastructure side has already proven that it is possible to deliver the ability to pay for compute on an hourly or more granular basis.

Posted May 15, 2017

What are the enabling technologies that make enterprise architecture what it is today? There are a range of new-generation technologies and approaches shaping today's data environments. The key is putting them all together to help enterprise architecture fit into the enterprise's vision of itself as a data-driven organization. Tools and technologies emerging within today's data-driven enterprise include cloud, data lakes, real-time analytics, microservices, containers, Spark, Hadoop, and open source trends.

Posted May 15, 2017

Many companies are beginning to acquire IoT data and more external datasets for new forms of analytics. However, they are realizing the value in integrating this data with their existing operational systems and databases. This has given way to a demand for new architecture patterns and data engineering best practices that are being incorporated into cloud and hybrid cloud strategies.

Posted May 11, 2017

Dell EMC is announcing new data backup and protection solutions to enable customers to ensure data is secure, backed up and protected against disasters and outages.

Posted May 09, 2017

Advanced Systems Concepts, Inc. (ASCI) has released an update to its flagship platform that adds support for Hadoop ecosystem as well as workflow performance. ActiveBatch Version 11 is designed to get data into the hands of end users in real-time.

Posted May 08, 2017

Confluent, a provider of a streaming platform based on Apache Kafka, is rolling out Confluent Cloud, a fully managed streaming data service aimed at helping developers to focus on building streaming applications with Apache Kafka, rather than Kafka operations. Currently available via an early access program, the Confluent Cloud service will initially be available in Amazon Web Services, with support for Microsoft Azure and Google Cloud to be added in the future.

Posted May 08, 2017

Hadoop and NoSQL databases have emerged as leading choices to capture and analyze big data by bringing new capabilities to the field of data management and analysis. At the same time, the relational database, firmly entrenched in most enterprises, continues to advance in features and varieties to address new challenges.

Posted May 05, 2017

Data security has been the source of dramatic changes in the last 10 years, influencing technologies and the way businesses operate globally. Data Summit 2017 will take a deep dive into evolving enterprise security considerations during the Data Security Forum moderated by Michelle Malcher, security architect at Extreme Scale Solutions. Data Summit 2017 takes place May 16-17 at the New York Hilton Midtown, with pre-conference workshops on May 15.

Posted May 05, 2017

Cloudera, which last week began trading on the New York Stock Exchange under the symbol "CLDR," has announced the general availability of the Cloudera Data Science Workbench, a self-service tool for data scientists. The workbench, which was announced in beta at Strata+Hadoop World San Jose 2017, enables fast, easy and secure self-service data science for the enterprise.

Posted May 02, 2017

Cloudera, a provider of a platform for machine learning and advanced analytics built on open source technologies including Hadoop, launched an IPO and is beginning public trading on the New York Stock Exchange under the symbol "CLDR."

Posted April 28, 2017

Voting has opened for the 2017 Database Trends and Applications Readers' Choice Awards. Unlike other awards programs that rely on our editorial staff's evaluations, the DBTA Readers' Choice Awards are unique in that the winning information management solutions are chosen by you - the people who actually use them.

Posted April 26, 2017

With the increasing volume, variety, and velocity of big data flowing into enterprises, they no longer have the ability to govern and synchronize all of their information. As a result, new processes must be put in place to quickly explore and assess data for value, says Joe Caserta, CEO and founder of Caserta Concepts. Caserta will present a keynote as well as a workshop at Data Summit 2017.

Posted April 24, 2017

MicroStrategy is partnering with Alation, offering users of Alation Data access to a data catalog directly within the MicroStrategy interface that can seamlessly conduct self-service enterprise data discovery and analytics in the MicroStrategy platform. When Alation connects to an organization's data sources, it crawls and indexes data assets stored across different physical repositories, including databases, Hadoop files and data visualization tools, to produce a rich catalog.

Posted April 18, 2017

As mobile has pushed deeper into enterprises, there is a growing recognition that it may be possible to run significant parts of businesses from relatively small devices. While mobile devices may not be ready to run entire enterprises, in many cases, they certainly can run more limited functions.

Posted April 18, 2017

Hewlett Packard Enterprise (HPE) is announcing its HPE SecureData platform has achieved the industry's Federal Information Processing Standard (FIPS) 140-2 validation of Format-Preserving Encryption (FPE). HPE SecureData has the world's first FIPS-validated AES-FF1 encryption configuration option to operate in strict FIPS mode, according to the vendor.

Posted April 13, 2017

Innovative technologies, such as artificial intelligence, augmented reality, robotics, and IoT, have had, and will continue to have, broad impact that we don't yet fully understand. Organizations that adopt these technologies will require new business models and processes. We will need to understand who our customers are and what they expect. The world of work as we know it today will continue to evolve at a faster pace—this is why adaptability and resilience are critical to a vibrant career.

Posted April 12, 2017

MapR Technologies has released an updated version of the MapR Ecosystem Pack (MEP) program, a set of open source ecosystem projects that support applications running on the MapR Converged Data Platform with inter-project compatibility.

Posted April 10, 2017

By now we are all in agreement: The business of data is changing. Business users are more empowered to work with data; IT is becoming less about control and more about enablement. New data science job descriptions—such as the data scientist—are springing up as companies everywhere look for the right people with the right skill sets to squeeze more value from their data. Data itself is getting bigger, hardware more economical, and analytical software more "self-service." We've embraced the paradigm shift from traditional BI to iterative data discovery. It's a new era.

Posted April 07, 2017

As the Internet of Things (IoT) revolution works its way through marketing hype and seeks its place of valuable contribution within companies and industries, you might pause to wonder how IoT can create opportunities for your company. Yet that assessment is difficult in part because the buzz does not always align with reality. In short, it's no simple task to discern the true potential of IoT today, leaving one to wonder: What is realistic, what difference could IoT make in my company, and how mature are other companies in embracing IoT potential?

Posted April 07, 2017

The concept of data lakes is a great one, but if not done correctly, this treasure trove of information can quickly turn into a black abyss for data analysts and scientists, let alone business users.

Posted April 07, 2017

Make no mistake: Big data is promising, exciting, and effective—when done right. Once considered an overhyped buzzword, it's now a potential tool that leaders in every vertical want to harness. Unfortunately, the majority of new big data projects—about 55% of them, according to Gartner—are shuttered before they even get off the ground.

Posted April 07, 2017

There has been a sea of change in how enterprises are thinking about Apache Hadoop and big data. Today, a majority of enterprises are thinking about the cloud first, not on-premises, and are increasingly relying on ecosystem standards to drive their Apache Hadoop distribution selection.

Posted April 07, 2017

It often seems that working around things is a full-time task in every area of information technology. When workarounds are conceived and deployed, people are not always in agreement.

Posted April 07, 2017

It is difficult to find someone not talking about or considering using containers to deploy and manage their enterprise applications. A container just looks like another process running on a system; a dedicated CPU and pre-allocated memory aren't required in order to run a container. The simplicity of building, deploying, and managing containers is among the reasons that containers are growing rapidly in popularity.

Posted April 07, 2017

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