Key-Object – A New Paradigm in Search?

@machinelearnbot

Summary: The premise of this new Key Object architecture is that search is broken, at least as it applies to complex merchandise like computers, printers, and cameras. An innovative and workable solution is described. The question remains, is the pain sufficient to justify a switch? As we are all fond of saying, innovation follows pain points. Are we missing something in our uber-critical search capabilities that needs to be resolved?


Key-Object – A New Paradigm in Search?

@machinelearnbot

As we are all fond of saying, innovation follows pain points. Are we missing something in our uber-critical search capabilities that needs to be resolved? A colleague recently pointed me to a slim volume "Structured Search for Big Data" by Mikhail Gilula (published by Elsevier and available on Amazon) that argues that not only are our search tools deficient but that a complete revamp of the underlying key-word NoSQL DB structure is what's required. Use Google, Amazon, or any of the other life-critical search tools we've become so reliant upon and you are using key-word search on NoSQL. The pain that Gilula identifies is the length of time it takes the consumer to research and select complex merchandise for best deals resulting from the imprecision of the search results.


On RDBMS, NoSQL and NewSQL databases. Interview with John Ryan

@machinelearnbot

"The single most important lesson I've learned is to keep it simple. I find designers sometimes deliver over-complex, generic solutions that could (in theory) do anything, but in reality are remarkably difficult to operate, and often misunderstood."–John I have interviewed John Ryan, Data Warehouse Solution Architect (Director) at UBS. You are an experienced Data Warehouse architect, designer and developer. What are the main lessons you have learned in your career?


Hadoop vs. NoSql vs. Sql vs. NewSql By Example

@machinelearnbot

Although Mainframe Hierarchical Databases are very much alive today, The Relational Databases (RDBMS) (SQL) have dominated the Database market, and they have done a lot of good. The reason the money we deposit doesn't go to someone else's account, our airline reservation ensures that we have a seat on the plane, or we are not blamed for something we didn't do, etc… RDBMS' data integrity is due to its adherence to ACID (atomicity, consistency, isolation, and durability) principles. Web technology started the revolution. RDBMS was not designed to handle the number of transactions that take place on Amazon every second. The primary constraining factor was RDBMS' schema.


Hadoop vs. NoSql vs. Sql vs. NewSql By Example

@machinelearnbot

Although Mainframe Hierarchical Databases are very much alive today, The Relational Databases (RDBMS) (SQL) have dominated the Database market, and they have done a lot of good. The reason the money we deposit doesn't go to someone else's account, our airline reservation ensures that we have a seat on the plane, or we are not blamed for something we didn't do, etc… RDBMS' data integrity is due to its adherence to ACID (atomicity, consistency, isolation, and durability) principles. Web technology started the revolution. RDBMS was not designed to handle the number of transactions that take place on Amazon every second. The primary constraining factor was RDBMS' schema.