no doubt you've heard about nosql databases and how they're used religiously by many high-tech companies but what are nosql databases and what makes them so different from the relational or sql databases you're used tonosql is short for not only structured query languagebut although it' true that nosql databases can allow you to query them with sqlyou don' have to focus on the actual name much debate has already raged over the name and whether this group of new databases should even have collective name at all ratherlet' look at what they represent as opposed to relational database management systems (rdbmstraditional databases reside on single computer or server this used to be fine as long as your data didn' outgrow your serverbut it hasn' been the case for many companies for long time now with the growth of the internetcompanies such as google and amazon felt they were held back by these single-node databases and looked for alternatives numerous companies use single-node nosql databases such as mongodb because they want the flexible schema or the ability to hierarchically aggregate data here are several early examplesgoogle' first nosql solution was google bigtablewhich marked the start of the columnar databases amazon came up with dynamoa key-value store two more database types emerged in the quest for partitioningthe document store and the graph database we'll go into detail on each of the four types later in the please note thatalthough size was an important factorthese databases didn' originate solely from the need to handle larger volumes of data every of big data has influence (volumevarietyvelocityand sometimes veracitygraph databasesfor instancecan handle network data graph database enthusiasts even claim that everything can be seen as network for examplehow do you prepare dinnerwith ingredients these ingredients are brought together to form the dish and can be used along with other ingredients to form other dishes seen from this point of viewingredients and recipes are part of network but recipes and ingredients could also be stored in your relational database or document storeit' all how you look at the problem herein lies the strength of nosqlthe ability to look at problem from different angleshaping the data structure to the use case as data scientistyour job is to find the best answer to any problem although sometimes this is still easier to attain using rdbmsoften particular nosql database offers better approach are relational databases doomed to disappear in companies with big data because of the need for partitioningnonewsql platforms (not to be confused with nosqlare the rdbms answer to the need for cluster setup newsql databases follow the relational model but are capable of being divided into distributed cluster like nosql see see