JSON is a text-based format, and text parsing is very slow
JSON’s readable format is far from space-efficient, another database
JSON only supports a limited number of basic data types
In order to make MongoDB JSON-first, but still high-performance and general-purpose, BSON was
invented to bridge the gap: a binary representation to store data in JSON format, optimized for
speed, space, and flexibility. It
’
s not dissimilar from other interchange formats like protocol
buffers, or thrift, in terms of approach.
BSON simply stands for “Binary JSON,” and that’s exactly what it was
invented to be. BSON’s binary structure encodes type and length
information, which allows it to be parsed much more quickly.
Since its initial formulation, BSON has been extended to add some optional
non-JSON-native data types, like dates and binary data, without which
MongoDB would have been missing some valuable support.
Languages that support any kind of complex mathematics typically have
different sized integers (ints vs longs) or various levels of decimal
precision (float, double, decimal128, etc.).
Not only is it helpful to be able to represent those distinctions in data
stored in MongoDB, it also allows for comparisons and calculations to
happen directly on data in ways that simplify consuming application code.
Does MongoDB use BSON, or JSON?
MongoDB stores data in BSON format both internally, and over the network,
but that doesn’t mean you can’t think of MongoDB as a JSON database.
Anything you can represent in JSON can be natively stored in MongoDB, and
retrieved just as easily in JSON.
The following are some example documents (in JavaScript / Python style
syntax) and their corresponding BSON representations.
Unlike systems that simply store JSON as string-encoded values, or binary-
encoded blobs, MongoDB uses BSON to offer the industry’s most powerful
indexing and querying features on top of the web’s most usable data
For example, MongoDB allows developers to query and manipulate objects by
specific keys inside the JSON/BSON document, even in nested documents many
layers deep into a record, and create high performance indexes on those
When using a MongoDB driver in your language of choice, it’s still
important to know that you’re accessing BSON data through the abstractions
available in that language.
Firstly, BSON objects may contain Date or Binary objects that are not
natively representable in pure JSON. Second, each programming language has
its own object semantics. JSON objects have ordered keys, for instance,
while Python dictionaries (the closest native data structure that’s
analogous to JavaScript Objects) are unordered, while differences in
numeric and string data types can also come into play. Third, BSON supports
a variety of numeric types that are not native to JSON, and each language
will represent these differently.
Check your
driver documentation
to make sure you understand how to best
access MongoDB BSON-backed data in your language to avoid confusion, and
get the most out of your MongoDB experience.
String, Boolean, Number (Integer, Float,
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