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http://www.databaserevolution.com/
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United States
View this contact
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Robin Bloor
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United States
View this contact
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Default Web Site Page | databaserevolution.com Reviews
https://databaserevolution.com
Research into current database technology
databaserevolution.com
DataStax and Cassandra Provide Key Value for Application Workloads
http://databaserevolution.com/2012/05/datastax
The Nature of Data. DataStax and Cassandra Provide Key Value for Application Workloads. May 31, 2012. Cassandra supports these requirements through a distributed architecture. The database runs on a cluster of identical commodity servers, making it suitable for cloud environments where servers can be added if the workload grows unexpectedly. A scale-out environment made up of many servers is going to have more failures in a year than a single-server environment. That’s a simple law of averages ...This is...
Michael Hunger and Philip Rathle
http://databaserevolution.com/author/michael-hunger-and-philip-rathle
The Nature of Data. Michael Hunger and Philip Rathle. NoSQL, Big Data and Graphs: Technology Choices for Today’s Mission-Critical Applications. By Michael Hunger and Philip Rathle. November 23, 2012. The New Database Revolution Findings Webcast. Big Data Analytics and NoSQL. Relational and Analytic Database Innovations. Get smart with the Thesis WordPress Theme.
The Database Revolution — Research into current database technology — Page 2
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The Nature of Data. Checklist for Leveraging Big Data Decisions. April 5, 2012. Read the full article →. Welcome to the Machine: How InfoBright Harnesses Big Data. March 28, 2012. Read the full article →. NoSQL Adoption: Benefits and Challenges. March 27, 2012. Read the full article →. Roundtable 2: Big Data Analytics and NoSQL. March 26, 2012. Read the full article →. Roundtable 1: What’s New With Relational? March 15, 2012. Read the full article →. The Species of Data. March 12, 2012. February 29, 2012.
Database Products
http://databaserevolution.com/articles/database-products
The Nature of Data. We list below a series of articles that focus on individual database products, primarily from the perspective of product architecture. Hortonworks and the Hadoop User. Using Columnar Databases to Deliver Near Real-Time Answers to Big Data Questions. DataStax and Cassandra Provide Key Value for Application Workloads. Notify me of followup comments via e-mail. You can also subscribe. Notify me of follow-up comments by email. Notify me of new posts by email. Big Data Analytics and NoSQL.
Business Intelligence
http://databaserevolution.com/articles/business-intelligence
The Nature of Data. Articles that discuss aspects of Business Intelligence and Analytics:. Big Data is Bigger than NoSQL. Is BI Too Hard For Us? Is BI’s Destiny In The Cloud? 10 Reasons Why The Cloud Is A Necessity. Notify me of followup comments via e-mail. You can also subscribe. Notify me of follow-up comments by email. Notify me of new posts by email. The New Database Revolution Findings Webcast. Big Data Analytics and NoSQL. Relational and Analytic Database Innovations.
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Media - Inside Analysis
http://insideanalysis.com/media
Making Sense of Analytics, BI and Big Data. Enterprise Hadoop in Production. Making Sense of Hadoop. Big Data Information Architecture. Designed for the busy professional who's looking to make a smart enterprise software purchase, or the innovative vendor who's looking to capture an audience, The Bloor Group produces both regular and occasional interactive webcasts. Austin, TX 78720. Subscribe to the Newsletter. To receive our weekly newsletter!
Uncategorized | Database Fog Blog
https://skylandtech.net/category/uncategorized
It is about Architecture… not about Marketing…. Who is How Columnar? Who is How Parallel? Today I am going to focus on a topic that I’ve suggested previously without the right emphasis: the new database architecture that uses vector processing on compressed columns to significantly accelerate performance. This is the final post inspired by Bityota (bityota.com). They reminded me that the use of vectors, once implemented by only a few vendors,…. April 30, 2015. High Performance Commercial Computing. For s...
How DBMS Vendors Admit to an Architectural Limitation: Part 3 – EDW on IBM z/OS | Database Fog Blog
https://skylandtech.net/2015/03/16/how-dbms-vendors-admit-to-an-architectural-limitation-part-3-edw-on-ibm-zos
It is about Architecture… not about Marketing…. Who is How Columnar? Who is How Parallel? How DBMS Vendors Admit to an Architectural Limitation: Part 3 – EDW on IBM z/OS. March 16, 2015. This is the 3rd and final example of a vendor admitting, without admitting, to an architectural limitation. The first two parts on Exadata and Teradata are here. Netezza Zone Maps and I/O Avoidance. DB2 BLU vs. Netezza and the Winner is. Wondering About Netezza and A Teradata Prediction Comes True. IBM Pure Data System.
Cloud Computing | Database Fog Blog
https://skylandtech.net/category/buzzwords/cloud-computing-buzzwords
It is about Architecture… not about Marketing…. Who is How Columnar? Who is How Parallel? A New Way of Thinking About EDW Federation. There is a new way to think about data warehouse architecture. The Gartner Group calls it a logical data warehouse and it uses database federation to dynamically integrate a universe of data warehouses, operational data stores, and data marts into a single, united, structure. This blog has suggested that there is a special case of the…. April 29, 2015. April 28, 2015.
Data Warehouse | Database Fog Blog
https://skylandtech.net/category/buzzwords/data-warehouse
It is about Architecture… not about Marketing…. Who is How Columnar? Who is How Parallel? Hadoop and Company Financial Performance. I have posted several times about the impact of the Hadoop eco-system on a several companies (here, here, here, for example). The topic cam up in a tweet thread a few weeks back… which prompts this quick note. Fours years ago the street price for a scalable, parallel, enterprise data warehouse platform was $US25K-$US35K per…. July 27, 2015. April 29, 2015. March 16, 2015.
Who is How Parallel? | Database Fog Blog
https://skylandtech.net/current-mpp-db-units-of-parallelism
It is about Architecture… not about Marketing…. Who is How Columnar? Who is How Parallel? Who is How Parallel? Recommends 1 Segment instance for each 2 cores. Maybe only 12 cannot find if they use hyper-threads. May use hyper-threads but limited by 16 FPGAs. A unit of parallelism (UoP) is defined as the maximum number of instructions that can execute in parallel on a single node for a single query. Since any program can start threads that wait I do not count these as UoP. On some CPUs. You are commenting...
Shared-nothing | Database Fog Blog
https://skylandtech.net/category/database-architecture/shared-nothing
It is about Architecture… not about Marketing…. Who is How Columnar? Who is How Parallel? A New Way of Thinking About EDW Federation. There is a new way to think about data warehouse architecture. The Gartner Group calls it a logical data warehouse and it uses database federation to dynamically integrate a universe of data warehouses, operational data stores, and data marts into a single, united, structure. This blog has suggested that there is a special case of the…. April 29, 2015. February 16, 2015.
Metadata | Database Fog Blog
https://skylandtech.net/category/metadata
It is about Architecture… not about Marketing…. Who is How Columnar? Who is How Parallel? Vendor Spin: What is not Metadata… What is not open…. I recently listened to a pitch by a vendor that was well spun. Let’s use this post to consider some spin around what is not metadata and what is a proprietary interface. The vendor described how they stored photos… I pointed out that photos were clearly not metadata… so they went on to talk about the…. March 23, 2015. Follow Blog via Email. Top Posts and Pages.
Getting Out of the Weeds: Self-Service Big Data Integration - Inside Analysis
http://insideanalysis.com/2015/05/getting-out-of-the-weeds-self-service-big-data-integration
Making Sense of Analytics, BI and Big Data. Enterprise Hadoop in Production. Making Sense of Hadoop. Big Data Information Architecture. Getting Out of the Weeds: Self-Service Big Data Integration. May 18, 2015. Unfortunately, that type of response is no longer acceptable. The current speed of business does not run in 12-18 month increments, but 12-18 week segments, if not faster. IT departments need to be more responsive to the business and to opportunities to gain advantage over the competition. When yo...
What Hadoop Is. What Hadoop Isn't. - Inside Analysis
http://insideanalysis.com/2012/12/what-hadoop-is-what-is-isnt
Making Sense of Analytics, BI and Big Data. Enterprise Hadoop in Production. Making Sense of Hadoop. Big Data Information Architecture. What Hadoop Is. What Hadoop Isn’t. December 7, 2012. Watch Mark Madsen and Hortonworks in The Briefing Room. Mark Madsen is President of third Nature. He focuses on strategy and design for analytics and competitive uses of information, especially new and emerging technology and practices in these areas. His experience covers a broad range of activities, including...8230;...
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Database resumes
Resume: Your Marketing Piece. August 21, 2011. How to Write a Great Resume : Highlighting Accomplishments on Resumes. Resume Writing: Get Started. August 18, 2011. Resume Writing: Get Started. How to Write a Great Resume : Highlighting Accomplishments on Resumes. Highlighting Accomplishments on Resumes. August 15, 2011. How to Write a Great Resume : Highlighting Accomplishments on Resumes. Resume Objectives, Summaries and Profiles. August 12, 2011. Resume Tips – Your Resume Objective Section.
Databaseretrieval.com
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databasereverseengineering.com
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Ricette da Cucina - La raccolta DEFINITIVA!
Ricette da Cucina - La raccolta DEFINITIVA! MANGIARE BENE e' anche FACILE! Domenica 11 marzo 2007. Giapponese - Ramen FACILE DA PREPARARE. 500g di somen o soba (o spaghetti di riso nostrani). 150g di pancetta affumicata. 5 foglie di costa con il gambo (FACOLTATIVO). Dado o Dashi (brodo di base della cucina giappones, è fatto di alghe e pesce esiccati ed è disponibile in confezioni già pronte, sia grattugiato sia in granuli, oppure in fiocchi a cui si deve aggiungere acqua bollente). 80 gr di carote.
We produce the data - Database Ridge - We Own the Data
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