MongoDB is the world’s most popular document database with powerful capabilities like full-text search, geospatial queries, data aggregation, and more https://bit.ly/3rbFIpG

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🔗 Resources

MongoDB Atlas https://bit.ly/3rbFIpG
MongoDB on Github https://github.com/mongodb/mongo
2024-02-04T05:49:01.078Z
nova-2
2-general-nova
2024-01-09.29447
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67875a7f-c9c4-48a0-aa55-5bdb8a91c34a
deprecated
MongoDB is the world's most advanced and popular document oriented database.
It was created in 2007 after the team at DoubleClick, a company serving 400,000 ads per second, faced issues with scalability and flexibility using existing database systems.
This inspired them to design a database where all data is stored in JSON like documents, which are organized into collections where they can be queried.
Unlike a relational table, a predefined schema for a collection is optional, which allows you to evolve your data structures rapidly without running complex database migrations.
But more importantly, it allows data that's frequently accessed together by an app to be stored in the same place.
This makes read operations extremely fast because no joins are required.
It's like having a fully assembled car ready to go as opposed to joining together a bunch of separate parts.
And that also makes the database much easier to scale horizontally via sharding.
Unlike relational tables, collections are self contained, making them much easier to work with in a distributed system.
That's why they call it Mongo.
It's designed for humongous workloads.
When you create a new document in MongoDB, it's assigned an object ID that's unique to that collection.
Inside the document, you can define multiple fields where the value might be a variety of different data types like a string, array, object, and so on.
Now to work with your data in any programming language, the query API is used to perform basic read and write operations as well as complex queries and transformations across the database.
To optimize performance, secondary indexes can be created to make common queries extremely fast.
It also supports geospatial queries to find all the documents near a geographic location.
In addition to queries, ease, you can also create data aggregation pipelines, which can group documents together and reduce them to a single result.
MongoDB is free to use and can be self hosted.
But the quickest way to get started is with the free tier on Atlas.
It scales automatically and provides a UI where you can interact with your data, plus a ton of other awesome features like full text search that leverages the power of Apache Lucene.
In addition, they just launched a serverless option where you only pay for the exact resources that you use.
And Atlas has other essential features like triggers that make it easy to run serverless functions when your underlying data changes.
Then there's Realm, which is a Firebase like platform that makes it easy to sync up your data with a front end application in real time.
This has been MongoDB in 100 seconds.
Let me know know if you want to see a full tutorial in the comments.
Thanks for watching, and I will see you in the next one.

Speaker 0: MongoDB is the world's most advanced and popular document oriented database. It was created in 2007 after the team at DoubleClick, a company serving 400,000 ads per second, faced issues with scalability and flexibility using existing database systems. This inspired them to design a database where all data is stored in JSON like documents, which are organized into collections where they can be queried. Unlike a relational table, a predefined schema for a collection is optional, which allows you to evolve your data structures rapidly without running complex database migrations. But more importantly, it allows data that's frequently accessed together by an app to be stored in the same place.

This makes read operations extremely fast because no joins are required. It's like having a fully assembled car ready to go as opposed to joining together a bunch of separate parts. And that also makes the database much easier to scale horizontally via sharding. Unlike relational tables, collections are self contained, making them much easier to work with in a distributed system. That's why they call it Mongo.

It's designed for humongous workloads. When you create a new document in MongoDB, it's assigned an object ID that's unique to that collection. Inside the document, you can define multiple fields where the value might be a variety of different data types like a string, array, object, and so on. Now to work with your data in any programming language, the query API is used to perform basic read and write operations as well as complex queries and transformations across the database. To optimize performance, secondary indexes can be created to make common queries extremely fast.

It also supports geospatial queries to find all the documents near a geographic location. In addition to queries, ease, you can also create data aggregation pipelines, which can group documents together and reduce them to a single result. MongoDB is free to use and can be self hosted. But the quickest way to get started is with the free tier on Atlas. It scales automatically and provides a UI where you can interact with your data, plus a ton of other awesome features like full text search that leverages the power of Apache Lucene.

In addition, they just launched a serverless option where you only pay for the exact resources that you use. And Atlas has other essential features like triggers that make it easy to run serverless functions when your underlying data changes. Then there's Realm, which is a Firebase like platform that makes it easy to sync up your data with a front end application in real time. This has been MongoDB in 100 seconds. Let me know know if you want to see a full tutorial in the comments.

Thanks for watching, and I will see you in the next one.
MongoDB is the world's most advanced and popular document oriented database. It was created in 2007 after the team at DoubleClick, a company serving 400,000 ads per second, faced issues with scalability and flexibility using existing database systems. This inspired them to design a database where all data is stored in JSON like documents, which are organized into collections where they can be queried. Unlike a relational table, a predefined schema for a collection is optional, which allows you to evolve your data structures rapidly without running complex database migrations. But more importantly, it allows data that's frequently accessed together by an app to be stored in the same place. This makes read operations extremely fast because no joins are required.
databases
data management
It's like having a fully assembled car ready to go as opposed to joining together a bunch of separate parts. And that also makes the database much easier to scale horizontally via sharding. Unlike relational tables, collections are self contained, making them much easier to work with in a distributed system. That's why they call it Mongo. It's designed for humongous workloads. When you create a new document in MongoDB, it's assigned an object ID that's unique to that collection. Inside the document, you can define multiple fields where the value might be a variety of different data types like a string, array, object, and so on. Now to work with your data in any programming language, the query API is used to perform basic read and write operations as well as complex queries and transformations across the database. To optimize performance, secondary indexes can be created to make common queries extremely fast. It also supports geospatial queries to find all the documents near a geographic location. In addition to queries, ease, you can also create data aggregation pipelines, which can group documents together and reduce them to a single result. MongoDB is free to use and can be self hosted. But the quickest way to get started is with the free tier on Atlas. It scales automatically and provides a UI where you can interact with your data, plus a ton of other awesome features like full text search that leverages the power of Apache Lucene. In addition, they just launched a serverless option where you only pay for the exact resources that you use.
databases
programming
data management
mining
And Atlas has other essential features like triggers that make it easy to run serverless functions when your underlying data changes.
Then there's Realm, which is a Firebase like platform that makes it easy to sync up your data with a front end application in real time. This has been MongoDB in 100 seconds. Let me know know if you want to see a full tutorial in the comments. Thanks for watching, and I will see you in the next one.
databases
MongoDB is the world's most advanced and popular document oriented database. It was created in 2007 after the team at DoubleClick, a company serving 400,000 ads per second, faced issues with scalability and flexibility using existing database systems. This inspired them to design a database where all data is stored in JSON like documents, which are organized into collections where they can be queried. Unlike a relational table, a predefined schema for a collection is optional, which allows you to evolve your data structures rapidly without running complex database migrations. But more importantly, it allows data that's frequently accessed together by an app to be stored in the same place. This makes read operations extremely fast because no joins are required. It's like having a fully assembled car ready to go as opposed to joining together a bunch of separate parts. And that also makes the database much easier to scale horizontally via sharding. Unlike relational tables, collections are self contained, making them much easier to work with in a distributed system. That's why they call it Mongo. It's designed for humongous workloads. When you create a new document in MongoDB, it's assigned an object ID that's unique to that collection. Inside the document, you can define multiple fields where the value might be a variety of different data types like a string, array, object, and so on. Now to work with your data in any programming language, the query API is used to perform basic read and write operations as well as complex queries and transformations across the database. To optimize performance, secondary indexes can be created to make common queries extremely fast. It also supports geospatial queries to find all the documents near a geographic location. In addition to queries, ease, you can also create data aggregation pipelines, which can group documents together and reduce them to a single result. MongoDB is free to use and can be self hosted. But the quickest way to get started is with the free tier on Atlas. It scales automatically and provides a UI where you can interact with your data, plus a ton of other awesome features like full text search that leverages the power of Apache Lucene. In addition, they just launched a serverless option where you only pay for the exact resources that you use. And Atlas has other essential features like triggers that make it easy to run serverless functions when your underlying data changes. Then there's Realm, which is a Firebase like platform that makes it easy to sync up your data with a front end application in real time. This has been MongoDB in 100 seconds. Let me know know if you want to see a full tutorial in the comments. Thanks for watching, and I will see you in the next one.
MongoDB
mongodb
is
is
the
the
world's
world's
most
most
advanced
advanced
and
and
popular
popular
document
document
oriented
oriented
database.
database
It
it
was
was
created
created
in
in
2007
2007
after
after
the
the
team
team
at
at
DoubleClick,
doubleclick
a
a
company
company
serving
serving
400,000
400,000
ads
ads
per
per
second,
second
faced
faced
issues
issues
with
with
scalability
scalability
and
and
flexibility
flexibility
using
using
existing
existing
database
database
systems.
systems
This
this
inspired
inspired
them
them
to
to
design
design
a
a
database
database
where
where
all
all
data
data
is
is
stored
stored
in
in
JSON
json
like
like
documents,
documents
which
which
are
are
organized
organized
into
into
collections
collections
where
where
they
they
can
can
be
be
queried.
queried
Unlike
unlike
a
a
relational
relational
table,
table
a
a
predefined
predefined
schema
schema
for
for
a
a
collection
collection
is
is
optional,
optional
which
which
allows
allows
you
you
to
to
evolve
evolve
your
your
data
data
structures
structures
rapidly
rapidly
without
without
running
running
complex
complex
database
database
migrations.
migrations
But
but
more
more
importantly,
importantly
it
it
allows
allows
data
data
that's
that's
frequently
frequently
accessed
accessed
together
together
by
by
an
an
app
app
to
to
be
be
stored
stored
in
in
the
the
same
same
place.
place
This
this
makes
makes
read
read
operations
operations
extremely
extremely
fast
fast
because
because
no
no
joins
joins
are
are
required.
required
It's
it's
like
like
having
having
a
a
fully
fully
assembled
assembled
car
car
ready
ready
to
to
go
go
as
as
opposed
opposed
to
to
joining
joining
together
together
a
a
bunch
bunch
of
of
separate
separate
parts.
parts
And
and
that
that
also
also
makes
makes
the
the
database
database
much
much
easier
easier
to
to
scale
scale
horizontally
horizontally
via
via
sharding.
sharding
Unlike
unlike
relational
relational
tables,
tables
collections
collections
are
are
self
self
contained,
contained
making
making
them
them
much
much
easier
easier
to
to
work
work
with
with
in
in
a
a
distributed
distributed
system.
system
That's
that's
why
why
they
they
call
call
it
it
Mongo.
mongo
It's
it's
designed
designed
for
for
humongous
humongous
workloads.
workloads
When
when
you
you
create
create
a
a
new
new
document
document
in
in
MongoDB,
mongodb
it's
it's
assigned
assigned
an
an
object
object
ID
id
that's
that's
unique
unique
to
to
that
that
collection.
collection
Inside
inside
the
the
document,
document
you
you
can
can
define
define
multiple
multiple
fields
fields
where
where
the
the
value
value
might
might
be
be
a
a
variety
variety
of
of
different
different
data
data
types
types
like
like
a
a
string,
string
array,
array
object,
object
and
and
so
so
on.
on
Now
now
to
to
work
work
with
with
your
your
data
data
in
in
any
any
programming
programming
language,
language
the
the
query
query
API
api
is
is
used
used
to
to
perform
perform
basic
basic
read
read
and
and
write
write
operations
operations
as
as
well
well
as
as
complex
complex
queries
queries
and
and
transformations
transformations
across
across
the
the
database.
database
To
to
optimize
optimize
performance,
performance
secondary
secondary
indexes
indexes
can
can
be
be
created
created
to
to
make
make
common
common
queries
queries
extremely
extremely
fast.
fast
It
it
also
also
supports
supports
geospatial
geospatial
queries
queries
to
to
find
find
all
all
the
the
documents
documents
near
near
a
a
geographic
geographic
location.
location
In
in
addition
addition
to
to
queries,
queries
ease,
ease
you
you
can
can
also
also
create
create
data
data
aggregation
aggregation
pipelines,
pipelines
which
which
can
can
group
group
documents
documents
together
together
and
and
reduce
reduce
them
them
to
to
a
a
single
single
result.
result
MongoDB
mongodb
is
is
free
free
to
to
use
use
and
and
can
can
be
be
self
self
hosted.
hosted
But
but
the
the
quickest
quickest
way
way
to
to
get
get
started
started
is
is
with
with
the
the
free
free
tier
tier
on
on
Atlas.
atlas
It
it
scales
scales
automatically
automatically
and
and
provides
provides
a
a
UI
ui
where
where
you
you
can
can
interact
interact
with
with
your
your
data,
data
plus
plus
a
a
ton
ton
of
of
other
other
awesome
awesome
features
features
like
like
full
full
text
text
search
search
that
that
leverages
leverages
the
the
power
power
of
of
Apache
apache
Lucene.
lucene
In
in
addition,
addition
they
they
just
just
launched
launched
a
a
serverless
serverless
option
option
where
where
you
you
only
only
pay
pay
for
for
the
the
exact
exact
resources
resources
that
that
you
you
use.
use
And
and
Atlas
atlas
has
has
other
other
essential
essential
features
features
like
like
triggers
triggers
that
that
make
make
it
it
easy
easy
to
to
run
run
serverless
serverless
functions
functions
when
when
your
your
underlying
underlying
data
data
changes.
changes
Then
then
there's
there's
Realm,
realm
which
which
is
is
a
a
Firebase
firebase
like
like
platform
platform
that
that
makes
makes
it
it
easy
easy
to
to
sync
sync
up
up
your
your
data
data
with
with
a
a
front
front
end
end
application
application
in
in
real
real
time.
time
This
this
has
has
been
been
MongoDB
mongodb
in
in
100
100
seconds.
seconds
Let
let
me
me
know
know
know
know
if
if
you
you
want
want
to
to
see
see
a
a
full
full
tutorial
tutorial
in
in
the
the
comments.
comments
Thanks
thanks
for
for
watching,
watching
and
and
I
i
will
will
see
see
you
you
in
in
the
the
next
next
one.
one
success
In this video, the speaker explains how MongoDB is created and how it can be used for fast workloads. They also discuss the benefits of using MongoDB for fast reads and write operations, as well as the use of schema and data aggregation pipelines. The speaker then introduces Realm, a reminded network platform that allows users to sync up data with a front end application in real time.
MongoDB in 100 Seconds
MongoDB is the world's most advanced and popular document oriented database. It was created in 2007 after the team at DoubleClick, a company serving 400,000 ads per second, faced issues with scalability and flexibility using existing database systems. This inspired them to design a database where all data is stored in JSON like documents, which are organized into collections where they can be queried. Unlike a relational table, a predefined schema for a collection is optional, which allows you to evolve your data structures rapidly without running complex database migrations. But more importantly, it allows data that's frequently accessed together by an app to be stored in the same place. This makes read operations extremely fast because no joins are required. It's like having a fully assembled car ready to go as opposed to joining together a bunch of separate parts. And that also makes the database much easier to scale horizontally via sharding. Unlike relational tables, collections are self contained, making them much easier to work with in a distributed system. That's why they call it Mongo. It's designed for humongous workloads. When you create a new document in MongoDB, it's assigned an object ID that's unique to that collection. Inside the document, you can define multiple fields where the value might be a variety of different data types like a string, array, object, and so on. Now to work with your data in any programming language, the query API is used to perform basic read and write operations as well as complex queries and transformations across the database. To optimize performance, secondary indexes can be created to make common queries extremely fast. It also supports geospatial queries to find all the documents near a geographic location. In addition to queries, ease, you can also create data aggregation pipelines, which can group documents together and reduce them to a single result. MongoDB is free to use and can be self hosted. But the quickest way to get started is with the free tier on Atlas. It scales automatically and provides a UI where you can interact with your data, plus a ton of other awesome features like full text search that leverages the power of Apache Lucene. In addition, they just launched a serverless option where you only pay for the exact resources that you use. And Atlas has other essential features like triggers that make it easy to run serverless functions when your underlying data changes. Then there's Realm, which is a Firebase like platform that makes it easy to sync up your data with a front end application in real time. This has been MongoDB in 100 seconds. Let me know know if you want to see a full tutorial in the comments. Thanks for watching, and I will see you in the next one.
In this video, the speaker explains how MongoDB is created and how it can be used for fast workloads. They also discuss the benefits of using MongoDB for fast reads and write operations, as well as the use of schema and data aggregation pipelines. The speaker then introduces Realm, a reminded network platform that allows users to sync up data with a front end application in real time.

        [INST]
        You are youtuber called Fireship you make engaging high-intensity and entertaining coding tutorials and tech news. 
        you covers a wide range of topics relevant to programmers, aiming to help them learn and improve their skills quickly.
        
        Given the title of the video : MongoDB in 100 Seconds 
        and a small summary : In this video, the speaker explains how MongoDB is created and how it can be used for fast workloads. They also discuss the benefits of using MongoDB for fast reads and write operations, as well as the use of schema and data aggregation pipelines. The speaker then introduces Realm, a reminded network platform that allows users to sync up data with a front end application in real time.
        [/INST]
        
        Generate the video : MongoDB is the world's most advanced and popular document oriented database. It was created in 2007 after the team at DoubleClick, a company serving 400,000 ads per second, faced issues with scalability and flexibility using existing database systems. This inspired them to design a database where all data is stored in JSON like documents, which are organized into collections where they can be queried. Unlike a relational table, a predefined schema for a collection is optional, which allows you to evolve your data structures rapidly without running complex database migrations. But more importantly, it allows data that's frequently accessed together by an app to be stored in the same place. This makes read operations extremely fast because no joins are required. It's like having a fully assembled car ready to go as opposed to joining together a bunch of separate parts. And that also makes the database much easier to scale horizontally via sharding. Unlike relational tables, collections are self contained, making them much easier to work with in a distributed system. That's why they call it Mongo. It's designed for humongous workloads. When you create a new document in MongoDB, it's assigned an object ID that's unique to that collection. Inside the document, you can define multiple fields where the value might be a variety of different data types like a string, array, object, and so on. Now to work with your data in any programming language, the query API is used to perform basic read and write operations as well as complex queries and transformations across the database. To optimize performance, secondary indexes can be created to make common queries extremely fast. It also supports geospatial queries to find all the documents near a geographic location. In addition to queries, ease, you can also create data aggregation pipelines, which can group documents together and reduce them to a single result. MongoDB is free to use and can be self hosted. But the quickest way to get started is with the free tier on Atlas. It scales automatically and provides a UI where you can interact with your data, plus a ton of other awesome features like full text search that leverages the power of Apache Lucene. In addition, they just launched a serverless option where you only pay for the exact resources that you use. And Atlas has other essential features like triggers that make it easy to run serverless functions when your underlying data changes. Then there's Realm, which is a Firebase like platform that makes it easy to sync up your data with a front end application in real time. This has been MongoDB in 100 seconds. Let me know know if you want to see a full tutorial in the comments. Thanks for watching, and I will see you in the next one.
        