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by petepete
2140 days ago
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Another huge win for SQL is that it's easy to construct from parts. You can very easily run and debug your subquery or common table expression on its own before combining it into a larger, more-complex query. If you (as I usually do) create plenty of views while analysing a dataset, the approach can be extremely powerful. Doing the same in JavaScript is possible, but it's slow and cumbersome by comparison. |
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MongoDB queries, while being interpretable by javascript, aren't really javascript. You can't interact with the data using javascript (well, you can, using eval, but you shouldn't). You interact with the data via the query language, which is, again, expressed in JS, just like SQL is expressed in English.
It's more accurate to consider the Aggregation Pipeline as being the "composable" system to get at data in MongoDB. And its exceedingly composable; far more than SQL. It's literally a pipeline; a series of steps which fetch, mutate, filter, map, limit, calculate, correlate, relate, and otherwise interact with the data in a database. Each step operates on the output of the previous step, in series. You can programmatically swap steps in-and-out, in production, with no string manipulation or ORM, debug each step in series, remove steps, see the output, get performance characteristics on each step. There's no complex black-boxed query execution planner or compiler, because the query plan is the pipeline.