NoSQL database systems are often highly optimized for retrieval and appending operations and often offer little functionality beyond record storage (e.g. key-value stores). The reduced run-time flexibility compared to full SQL systems is compensated by marked gains in scalability and performance for certain data models.

NoSQL is the acronym for Not Only SQL. The basic qualities of NoSQL databases are schemaless, distributed and horizontally scalable on commodity hardware. The NoSQL databases offers variety of functions to solve various problems with variety of data types, where “blob” used to be the only data type in RDBMS to store unstructured data.

Apr 9, 2010 · Document-based NoSQL databases (e.g. MongoDB, CouchDB); Key/Value NoSQL databases (e.g. Redis); Column family NoSQL databases (e.g. Hibase, Cassandra). What we call an Aggregate here, is what Eric Evans defined in its Domain-Driven Design as a self-sufficient of Entities and Value-Objects in a given Bounded Context.

NoSQL databases approach modelling from a different point of view generally. NoSQL modelling usually begins with asking questions on how the data in the database is going to be queried, so the main modelling is 'what are the list of questions that I want to ask of my database', whereas with SQL databases, modelling usually is a function of what ...

Jul 15, 2015 · NoSQL database systems are often highly optimized for retrieve and append operations and often offer little functionality beyond record storage (e.g. key-value stores). The reduced run time flexibility compared to full SQL systems is compensated by significant gains in scalability and performance for certain data models.

Apr 21, 2010 · NoSQL solutions usually manage relatively limited schemas with large cardinality in few entities, while data warehouses typically have lots of facts and dimensions (in a dimensional model) or lots of entities in a 3NF model.

Has anyone here have any experience deploying a real online system that had a full text search in any of the NoSQL databases? For example, how does the full-text search compare in MongoDB, Riak and CouchDB? Some of the metric that I am looking for is ease of deployment and maintaince and of course speed. How mature are they?

You are correct, the data is often stored de-normalized in NoSQL databases. The problem with the updates is partially where the term "eventual consistency" comes from. In your example, when you update the player's name (not a common event, but it can happen), you would issue a background job to update the name across all other records.

One can have a current NoSQL database and a historical NoSQL database. There will be a an nightly ETL ran everyday. This ETL will record every value with a timestamp, so instead of values it will always be tuples (versioned fields). It will only record a new value if there was a change made on the current value, saving space in the process.

ACID transactions are far more pessimistic i.e. they are more worried about data safety. In the NoSQL database world, ACID transactions are less fashionable as some databases have loosened the requirements for immediate consistency, data freshness and accuracy in order to gain other benefits, like scalability and resiliency. BASE stands for -