Course Outline

  1. File Document Storage (Cloud Storage)
    1. Features (OCR, Scalaibility, Search, etc...)
    2. Open Source examples (e.g. Next Cloud)
    3. Some commercial examples
  2. Flat file storage
    1. XML databases
    2. CSV databases
  3. Relational databases
    1. Normalization
    2. Dependencies and Constrants
    3. Scalability - replications, clusters
    4. Open Source and commercial software (MySQL, PostrgreSQL, DM7, Oracle, etc.)
  4. NoSQL Storage
    1. Document Oriented Databases (MongoDB, CouchDB etc...)
    2. Column Orientation (Canadra, Scylla etc...)
    3. Search Orientation (Elasticsearch...
  5. NewSQL
    1. CAP Theorem
    2. Opensource software (SequoiaDB, etc...)
  6. Search Engines
    1. Features (text processing, relevancy, etc...)
    2. Open Source examples
    3. Scalability, High Availability, Load Balacing, etc....
  7. Traditional Datawherehouses
    1. Business Inteligence, OLTP and Datawherehouse
    2. Opensource and commercial solutions
  8. MapReduce and Distributed Parallel Processing
    1. Hadoop-like (Hive, HFS, Impala)
  9. Distributed filesystem
    1. Overview of opensource (Ceph etc...)
  10. In-memory Databases
    1. Opensource solution (e.g. ApacheIgnite)
  11. Others
    1. Hypertable (Google Bigtable)
    2. BigQuery
    3. AWS solutsion (S3, etc...)
  12. Beyond present - future trends

Requirements

Though no technical background is required, understanding the examples requires some level of database theory (e.g. SQL, etc...)
  7 Hours
 

Need help picking the right course?
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Testimonials

I liked that he had actual know how of when to use each technology, that's valuable.

Radu Mazilu - eMAG IT Research
Which data storage to choose - from flat files, through SQL, NoSQL to massive distributed systems Course

The Trainer Subject Knowledge

Rares Serea - eMAG IT Research
Which data storage to choose - from flat files, through SQL, NoSQL to massive distributed systems Course

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