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Including NoSQL, Map-Reduce, Spark, big data, and more. This resource includes technical articles, books, training and general reading. Enjoy the reading!

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Here's the list (new additions, more than 30 articles marked with *):

  1. Hadoop: What It Is And Why It’s Such A Big Deal *
  2. The Big 'Big Data' Question: Hadoop or Spark? *
  3. NoSQL and RDBMS are on a Collision Course *
  4. Machine Learning at Scale with Spark *
  5. NoSQL & NewSQL Database Adoption 2014 *
  6. Big Data = 3 data issues *
  7. Embrace Relationships with Neo4J, R & Java *
  8. Hadoop Falcon and Data Lifecycle Management *
  9. Comparing MongoDB with MySQL *
  10. RethinkDB for Advanced Analytics *
  11. THE PAST (Entity-Attribute-Value) vs THE FUTURE (Sign, Signifier, Signified) *
  12. 18 Open Source NoSQL Databases *
  13. S3 instead of HDFS with Hadoop *
  14. Which one is best: R, SAS or Python, for data science? *
  15. Hadoop:- A soft Introduction *
  16. Big Data Analytics Beyond Hadoop: Real-Time Applications with Storm, Spark, and More Hadoop Alternatives *
  17. Ten top noSQL Databases *
  18. Survey: 'Big Data Paralysis' Is Holding Companies Back *
  19. Predictive Analytics and Data Science: Same or Different? *
  20. How Experian Is Using Big Data *
  21. 7 Amazing Big Data Myths *
  22. Deploy Hadoop Cluster *
  23. Why NoSQL became MORE SQL *
  24. The Big Data Tidal Wave - How Technology is Shaping the way Financial Services Companies Operate *
  25. Solving the Data Growth Crisis with Hadoop *
  26. Google F1 Database: One Step Closer To Discovering The DB Holy Grail *
  27. The Best Of Open Source For Big Data *
  28. The Emerging Data Stack and Mobile Access *
  29. Harnessing Big Data for Security: Intelligence in the Era of Cyber Warfare *
  30. New, fast Excel to process billions of rows via the cloud *
  31. Fake data science *
  32. Basic Understanding of Big Data. What is this and How it is going to solve complex problems *
  33. Lesson 9: Making Your Selection - Final Considerations *
  34. Great list of resources - NoSQL, Big Data, Machine Learning and more | GitHub 
  35. Implementing a Distributed Deep Learning Network over Spark 
  36. Correlation and R-Squared for Big Data 
  37. [Book] Big Data - Principles and best practices of scalable realtime data systems 
  38. 9 Lessons: Picking the Right NoSQL Tools 
  39. Lesson 2: NoSQL Databases are Good for Everything – Except Maybe this One Thing 
  40. 16 resources to learn and understand Hadoop 
  41. 8 Hadoop articles that you should read 
  42. Fast clustering algorithms for massive datasets 
  43. Hadoop – Whose to Choose 
  44. 11 Features any database, SQL or NoSQL, should have 
  45. Big Data: The 4 Layers Everyone Must Know 
  46. The Book: Big Data, NoSQL, Cloud A Paradigm Shift 
  47. Lesson 8: Graph Databases 
  48. How to get started with Hadoop? 
  49. Optimizing care gaps and outreach programs in Healthcare 
  50. Business Intelligence Architecture 
  51. Lesson 4: Features Common to (Most) NoSQL/NewSQL Databases 
  52. Get started with Hadoop and Spark in 10 minutes 
  53. Lesson 5: Key Value Stores (AKA 'Tuple' Stores) 
  54. How to score data in Hadoop/Hive in a flash 
  55. Interesting database questions 
  56. Lesson 3: Open Source, Distribution, or Suite 
  57. Big Data Applications Scaling Using Java Architecture in the Cloud 
  58. Lesson 7: Column Oriented Databases (aka Big Table or Wide Column) 
  59. Big Data Analytics Infrastructure 
  60. Hadoop Technology Stack 
  61. Lesson 6: Document Oriented Databases 
  62. A synthetic variance designed for Hadoop and big data 
  63. Practical illustration of Map-Reduce (Hadoop-style), on real data 
  64. Old SQL, New SQL, NoSQL - Making Sense of the Five Major Classes of Database Technology 
  65. How NoSQL Fundamentally Changed Machine Learning 
  66. eBook: Getting Started With Hadoop 
  67. Salaries for Hadoop professionals 
  68. Modern BI Architecture & Analytical Ecosystems 
  69. Wiley's Hadoop Book Bundle -- A Free 113 Page Sampler 
  70. Earthwatch to Look at Climate Change in Acadia National Park 
  71. Polyglot Persistence? 
  72. 50+ Open Source Tools for Big Data (See Anything Missing?) 
  73. Implementing a Distributed Deep Learning Network over Spark 
  74. Which one is best: R, SAS or Python, for data science? 
  75. 15+ Great Books for Hadoop 
  76. Clustering Similar Images Using MapReduce Style Feature Extraction with C# and R 
  77. A Comparison of NoSQL Offerings 
  78. How To Avoid The Big Data Quicksand 
  79. Deploy Hadoop Cluster 
  80. SQL to NoSQL translator 
  81. Programming for Data Science the Polyglot approach: Python + R + SQL 
  82. Seek the grail up the Knowledge Pyramid, not down 
  83. Big Data Logistics: data transfer using Apache Sqoop from RDBMS 

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