MongoDB Semantics

Now, I need to begin losing my relational vocabulary and start talking Mongo !

Some useful additional background here:
The MongoDB query language is not SQL, but 10gen describes it as a simple, expressive language with a straightforward syntax for efficient querying. Examples of simple query statements include “sum,” “min,” “max,” and “average.” These sorts of operators would be familiar to any database veteran or analyst, and they’re applied in a real-time data-processing pipeline that delivers sub-second performance, according to 10gen.

Other available query statements include “project,” which is used to select desired attributes and ignore everything else. “Group” lets you combine results with desired attributes. “Match” is a filter than can be used to eliminate documents from a query. “Limit,” “skip” and “sort,” are statements used in much the same way they’re used in SQL: to limit a query to a desired number of results, to skip over a given number of results, and to sort results alphabetically, numerically or by some other value.

SQL Terms/Concepts MongoDB Terms/Concepts
database database
table collection
row document or BSON document
column field
index index
table joins embedded documents and linking
primary keySpecify any unique column or column combination as primary key. primary keyIn MongoDB, the primary key is automatically set to the _idfield.
aggregation (e.g. group by) aggregation frameworkSee the SQL to Aggregation Framework Mapping Chart.

And query operators

WHERE $match
GROUP BY $group
HAVING $match
SELECT $project
ORDER BY $sort
LIMIT $limit
SUM() $sum
COUNT() $sum
join No direct corresponding operator; however, the $unwind operator allows for somewhat similar functionality, but with fields embedded within the document.

+ Some example query statements

SQL                                                           MongoDB


FROM users
WHERE status = "A"
    { status: "A" } )
FROM users
WHERE status = "A"
OR age = 50
    { $or: [ { status: "A" } ,
             { age: 50 } ] } )
FROM users
WHERE age > 25
AND   age <= 50
   { age: { $gt: 25, $lte: 50 } } )

And some really helpful analytical scenarios here




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