NoSQL Video Tutorials – 29 Hours
Here is a collection of over 29 hours of premium video tutorials on NoSQL by Pluralsight. In order to view the videos, you need to become a member of Pluralsight.
|
| A chart showing several of the SQL language elements that compose a single statement |
| By :User:SqlPac, modified by Ferdna – File:Sql statement anatomy.png, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=7557212 |
Background: NoSQL A NoSQL database originally referred to “non SQL” or “non relational” database. A NoSQL database provides a way to store and retrieve data that is modeled in means other than the tabular relations used in relational databases. These databases have existed since the late 1960s. However, they did not obtain the “NoSQL” name until the early 2000’s. This was triggered by the needs of Web 2.0 companies such as Facebook, Google and Amazon.com. NoSQL databases are being used more and more in big data and real-time web applications. NoSQL systems are also occasionally referred to as “Not only SQL.” This emphasizes that they may support SQL-like query languages.
The goals of NoSQL include: simplicity of design, simpler “horizontal” scaling to clusters of machines (which is a problem for relational databases), and finer control over availability. The data structures used by NoSQL databases (for example, key-value, wide column, graph, or document) are not the same as those used by default in relational databases, making some operations faster in NoSQL. The particular suitability of a given NoSQL database depends on the problem it must solve. Sometimes the data structures used by NoSQL databases are also viewed as “more flexible” than relational database tables.
Many NoSQL stores compromise consistency (in the sense of the CAP theorem) in favor of availability, partition tolerance, and speed. Barriers to the greater adoption of NoSQL stores include the use of low-level query languages (instead of SQL, for instance the lack of ability to perform ad-hoc JOINs across tables), lack of standardized interfaces, and huge previous investments in existing relational databases. Most NoSQL stores lack true ACID transactions, although a few databases, such as MarkLogic, Aerospike, FairCom c-treeACE, Google Spanner (though technically a NewSQL database), Symas LMDB and OrientDB have made them central to their designs. (See ACID and JOIN Support.)
Instead, most NoSQL databases offer a concept of “eventual consistency” in which database changes are propagated to all nodes “eventually” (typically within milliseconds) so queries for data might not return updated data immediately or might result in reading data that is not accurate, a problem known as stale reads. Additionally, some NoSQL systems may exhibit lost writes and other forms of data loss. Fortunately, some NoSQL systems provide concepts such as write-ahead logging to avoid data loss. For distributed transaction processing across multiple databases, data consistency is an even bigger challenge that is difficult for both NoSQL and relational databases. Even current relational databases “do not allow referential integrity constraints to span databases.” There are few systems that maintain both ACID transactions and X/Open XA standards for distributed transaction processing.
NoSQL
| Series | Title | Date | Presenter | Min |
|---|---|---|---|---|
| Administering an Elasticsearch Cluster | Administering an Elasticsearch Cluster | 12/11/2015 | JP Toto | 129 |
| MongoDB Administration | MongoDB Administration | 6/2/2015 | Nuri Halperin | 440 |
| Getting Started With Elasticsearch for .NET Developers | Getting Started With Elasticsearch for .NET Developers | 11/25/2014 | JP Toto | 115 |
| Big Data & Reporting with MongoDB | Big Data & Reporting with MongoDB | 4/28/2014 | Nuri Halperin | 147 |
| Riak Fundamentals | Riak Fundamentals | 11/12/2013 | Adron Hall | 87 |
| Introduction to MongoDB | Introduction to MongoDB | 7/11/2013 | Nuri Halperin | 147 |
| Building NoSQL Apps With Redis | Building NoSQL Apps With Redis | 7/9/2013 | John Sonmez | 199 |
| Big Data: The Big Picture | Big Data: The Big Picture | 10/31/2012 | Andrew Brust | 89 |
| NoSQL: The Big Picture | NoSQL: The Big Picture | 3/27/2012 | Andrew Brust | 71 |
| Understanding NoSQL | Understanding NoSQL | 2/10/2012 | Andrew Brust | 161 |
| Introduction to Raven DB | Introduction to Raven DB | 2/9/2012 | John Sonmez | 183 |
| Total | 1768 |
