From the course: Cleaning Data for Effective Data Science: Data Ingestion, Anomaly Detection, Value Imputation, and Feature Engineering
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NoSQL databases
Let's talk next about these so-called NoSQL databases, things other than RDBMSs. A number of database systems avoid the relational model, usually with the goal of better performance within a particular domain. As well, many RDBMSs now include JSON and XML data types, so there is some overlap now between so-called NoSQL and SQL databases at this point. In overview, these NoSQL systems break down roughly into document-oriented databases, graph databases, and key-value stores. Specific server software may combine elements of these or indeed elements of relational databases. And the specific performance characteristics, design philosophy, and general limitations vary among each project. Beyond mentioning here that they exist, I will not discuss in this lesson anything specific about data cleanliness issues that are characteristic of graph databases. The type of data analysis performed on graphs are typically somewhat specialized, but you may encounter these kinds of data in your…
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