Tag: Hadoop

Feed: IBM Big Data & Analytics Hub - All Content; Author: holly-vatter; The fusing of analytics with leading technologies can unlock significant business value and bring new transformation opportunities for enterprise companies. In order to be successful, analytics-based initiatives such as AI and the Internet of Things (IoT) need massive amounts of big data—and also the right applications to uncover hidden patterns, correlations and insights necessary to drive better data-driven decisions.Finding hidden data There are many reasons why siloed, unanalyzed data exists. Businesses will always struggle with integrating data following mergers and acquisitions; when extending data warehouses to include external ... Read More

Feed: Planet PostgreSQL. Built-in Sharding Architecture The build-in sharding feature in PostgreSQL is using the FDW based approach, the FDW’s are based on sql/med specification that defines how an external data source can be accessed from the PostgreSQL server. PostgreSQL provides number of foreign data wrapper (FDW’s) that are used for accessing external data sources, the postgres_fdw is used for accessing Postgres database running on external server, MySQL_fdw is used for accessing MySQL database from PG, MongoDB_fdw is used for accessing MongoDB and so on. The diagram below explains the current approach of built-in Sharding in PostgreSQL, the partitions are ... Read More

Feed: Planet PostgreSQL. Declarative Partitioning So far we have discussed scalability, what is scalability, why and when you need and what are the different types of scalability. Now we are starting to get into the meat of this topic and will discuss declarative partitioning and sharding in PostgreSQL. The sharding functionality is being laid on top of declarative partitioning functionality in PostgreSQL. Declarative partitioning was released in PostgreSQL 10, prior to declarative partitioning PostgreSQL was using table inheritance and plpgsql triggers for providing table partitioning. The example below shows how a table can be partitioned using the declarative partitioning syntax introduced ... Read More

Feed: MemSQL Blog. Author: Floyd Smith. In this webinar, which you can view here, MemSQL’s Mike Boyarski describes how real-time fraud detection represents a major digital initiative for banks. He shows how MemSQL gives fraud detection services, along with other real-time analytics, an edge with faster ingest, real-time scoring, and rapid response to a broader set of events. He also describes a major US bank’s implementation of this approach, which is described separately in our case study about fraud detection on the swipe. New Data Initiatives for Banks There’s a great deal of digital transformation occurring around data initiative for ... Read More

Feed: SAS Blogs. Author: Joe Furbee. Editor’s note: This is the first article in a series by Conor Hogan, a Solutions Architect at SAS, on SAS and database and storage options on cloud technologies. This article covers the SAS offerings available to connect to and interact with the various database options available in Amazon Web Services. As companies move their computing to the cloud, they are also moving their storage to the cloud. Just like compute in the cloud, data storage in the cloud is elastic and responds to demand while only paying for what you use. As more technologies ... Read More

Feed: Hadoop Dev. Author: Nagapriya Tiruthani. Announcing the immediate availability of Db2 Big SQL on Cloudera’s platform, CDH v6.2.  Extending the recent support on CDH v5, Db2 Big SQL will now add support to Cloudera Distributed Hadoop (CDH) v6.2 platform along with Hortonworks Data Platform (HDP) v2.6 & v3.1. Db2 Big SQL is an advanced SQL engine optimized for advanced analytics in a Big Data environment. IBM infuses the power of industry leading Db2 in open source technologies for machine learning, interactive, adhoc and batch analytics use cases.  The core capabilites of a mature SQL engine brings enterprise SQL capabilies to Big Data platform ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: holly-vatter; The best decisions are made by extracting value from all the disparate data across your business. Yet aggregating data across external sources, regional silos and various forms of storage is not an easy challenge to solve. Data-powered businesses need always-on access to data to keep operations moving smoothly and to stay competitive. As data infrastructures grow more distributed, many companies rely on complex hybrid and cloud environments, often from a combination of vendors and platforms across multiple regions. Companies with big data require solutions for continuous availability and ... Read More

Feed: CIO - MapR RSS feed. Author: Matt Asay. Cloud killed the fortunes of the Hadoop trinity—Cloudera, Hortonworks and MapR—and that same cloud likely won’t rain success down on Hewlett Packard Enterprise (HPE), which recently acquired the business assets of MapR.While the deal promises to marry “MapR’s technology, intellectual property, and domain expertise in artificial intelligence and machine learning (AI/ML) and analytics data management” with HPE’s “Intelligent Data Platform capabilities,” the deal is devoid of the one ingredient that both companies need most: cloud.The problem, in other words, isn’t that MapR wasn’t filled to the brim with smart folks and ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Jonathan Symonds. By Siddartha Mani, MinIO Few would argue with the statement that Hadoop HDFS is in decline. In fact, the HDFS part of the Hadoop ecosystem is in more than just decline - it is in freefall. At the time of its inception, it had a meaningful role to play as a high-throughput, fault-tolerant distributed file system. The secret sauce was data locality.  By co-locating compute and data on the same nodes, HDFS overcame the limitations of slow network access to data. The implications, however, are well known at this ... Read More

Feed: MemSQL Blog. Author: Floyd Smith. Wealth management is an intensely competitive offering for banks and other financial services institutions. It requires high concurrency – the ability to serve many users, fast – low latency, and the ability to access vast amounts of current and historical data in real time. Institutions have used in-memory databases and streaming data to try to meet the demand. In this webinar, MemSQL’s Sourabh Mehta shows how MemSQL improves the wealth management experience for users and gives institutions the ability to stand out in this competitive area. You can view the wealth management webinar here ... Read More