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Redis is an extremely fast in-memory database often used as a cache. It has evolved into a multi-model database with support for graphs, JSON documents, full-text search, and more. Try Redis Enterprise for free https://bit.ly/3wnVsXA

#database #tech #100SecondsOfCode

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🔗 Resources

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2024-02-04T05:49:45.693Z
nova-2
2-general-nova
2024-01-09.29447
30089e05-99d1-4376-b32e-c263170674af
8ba65fc6-954d-437b-ad22-15b8273b6c86
a3d7f28345f151a57a7065eca9211e551cb165e03a55caac04d2c95eb7f2b717
67875a7f-c9c4-48a0-aa55-5bdb8a91c34a
deprecated
Redis, an in memory multimodel database famous for its sub millisecond latency.
It was created in 2009 based on the idea that a cache can also be a durable data store.
Around this time, apps like Twitter were growing exponentially and needed a way to deliver data to their end on users faster than a relational database could handle.
Redis, which means remote dictionary server, was adopted by some of the most heavily traffic sites in the world because it changed the database game by creating a system where data is always modified or read from the main computer memory as opposed to the much slower disk.
But at the same time, it stores its data on the disk so it can be reconstructed as needed, which means the database is fully durable, supporting things like snapshots and backups.
Every data point in the database is a key followed by one of many different data structures, like a string, list, hash, or stream, so so you can store data naturally just like you would with your favorite programming language as opposed to squeezing it into a bunch of tables or JSON document.
At interacting with the database is handled with a simple set of commands like set followed by a key and value to create data, then get followed by a key to read data.
Historically, Redis has been described as a key value store and is often used as a cache to make relational databases faster at scale.
But here's where your mind is about to be blown.
Redis is perfectly suitable as a primary database, and can dramatically reduce complexity because making things go fast at scale is the primary cause of complexity in the first place.
With Redis, your database is already fast.
No need for a complex caching layer.
But you might be wondering, how do I model complex relationships?
Today, Redis is what you would call a multi model database, supporting a variety of different database paradigms with add on modules that you can opt into as needed.
If your data contains relationships, at Spring and Redis Graph and query it with Cypher or use the JSON module to structure your data as a hierarchy just like a document in an oriented database, then use the search module to turn your database into a full text search engine, and it even has modules for AI workloads, time series data, and more.
The quickest way to get started it is the free tier on Redis enterprise cloud.
That'll give you a free database to play around with and you can attach one extra module to it.
Then you can connect to it with the Redis CLI or with the Redis Insight tool, which contains an interactive dashboard to manage your data.
This has been Redis in 100 seconds.
But what do you guys think?
Would you use Redis as your primary database?
Let me know why or why not in the comments.
Thanks for watching, and I will see you in the next one.

Speaker 0: Redis, an in memory multimodel database famous for its sub millisecond latency. It was created in 2009 based on the idea that a cache can also be a durable data store. Around this time, apps like Twitter were growing exponentially and needed a way to deliver data to their end on users faster than a relational database could handle. Redis, which means remote dictionary server, was adopted by some of the most heavily traffic sites in the world because it changed the database game by creating a system where data is always modified or read from the main computer memory as opposed to the much slower disk. But at the same time, it stores its data on the disk so it can be reconstructed as needed, which means the database is fully durable, supporting things like snapshots and backups.

Every data point in the database is a key followed by one of many different data structures, like a string, list, hash, or stream, so so you can store data naturally just like you would with your favorite programming language as opposed to squeezing it into a bunch of tables or JSON document. At interacting with the database is handled with a simple set of commands like set followed by a key and value to create data, then get followed by a key to read data. Historically, Redis has been described as a key value store and is often used as a cache to make relational databases faster at scale. But here's where your mind is about to be blown. Redis is perfectly suitable as a primary database, and can dramatically reduce complexity because making things go fast at scale is the primary cause of complexity in the first place.

With Redis, your database is already fast. No need for a complex caching layer. But you might be wondering, how do I model complex relationships? Today, Redis is what you would call a multi model database, supporting a variety of different database paradigms with add on modules that you can opt into as needed. If your data contains relationships, at Spring and Redis Graph and query it with Cypher or use the JSON module to structure your data as a hierarchy just like a document in an oriented database, then use the search module to turn your database into a full text search engine, and it even has modules for AI workloads, time series data, and more.

The quickest way to get started it is the free tier on Redis enterprise cloud. That'll give you a free database to play around with and you can attach one extra module to it. Then you can connect to it with the Redis CLI or with the Redis Insight tool, which contains an interactive dashboard to manage your data. This has been Redis in 100 seconds. But what do you guys think?

Would you use Redis as your primary database? Let me know why or why not in the comments. Thanks for watching, and I will see you in the next one.
Redis, an in memory multimodel database famous for its sub millisecond latency. It was created in 2009 based on the idea that a cache can also be a durable data store. Around this time, apps like Twitter were growing exponentially and needed a way to deliver data to their end on users faster than a relational database could handle. Redis, which means remote dictionary server, was adopted by some of the most heavily traffic sites in the world because it changed the database game by creating a system where data is always modified or read from the main computer memory as opposed to the much slower disk. But at the same time, it stores its data on the disk so it can be reconstructed as needed, which means the database is fully durable, supporting things like snapshots and backups. Every data point in the database is a key followed by one of many different data structures, like a string, list, hash, or stream, so so you can store data naturally just like you would with your favorite programming language as opposed to squeezing it into a bunch of tables or JSON document. At interacting with the database is handled with a simple set of commands like set followed by a key and value to create data, then get followed by a key to read data. Historically, Redis has been described as a key value store and is often used as a cache to make relational databases faster at scale. But here's where your mind is about to be blown. Redis is perfectly suitable as a primary database, and can dramatically reduce complexity because making things go fast at scale is the primary cause of complexity in the first place. With Redis, your database is already fast. No need for a complex caching layer. But you might be wondering, how do I model complex relationships? Today, Redis is what you would call a multi model database, supporting a variety of different database paradigms with add on modules that you can opt into as needed. If your data contains relationships, at Spring and Redis Graph and query it with Cypher or use the JSON module to structure your data as a hierarchy just like a document in an oriented database, then use the search module to turn your database into a full text search engine, and it even has modules for AI workloads, time series data, and more. The quickest way to get started it is the free tier on Redis enterprise cloud. That'll give you a free database to play around with and you can attach one extra module to it. Then you can connect to it with the Redis CLI or with the Redis Insight tool, which contains an interactive dashboard to manage your data. This has been Redis in 100 seconds. But what do you guys think? Would you use Redis as your primary database? Let me know why or why not in the comments.
databases
data
software
data management
software development
internet
programming
data analysis
Thanks for watching, and I will see you in the next one.
Redis, an in memory multimodel database famous for its sub millisecond latency. It was created in 2009 based on the idea that a cache can also be a durable data store. Around this time, apps like Twitter were growing exponentially and needed a way to deliver data to their end on users faster than a relational database could handle. Redis, which means remote dictionary server, was adopted by some of the most heavily traffic sites in the world because it changed the database game by creating a system where data is always modified or read from the main computer memory as opposed to the much slower disk. But at the same time, it stores its data on the disk so it can be reconstructed as needed, which means the database is fully durable, supporting things like snapshots and backups. Every data point in the database is a key followed by one of many different data structures, like a string, list, hash, or stream, so so you can store data naturally just like you would with your favorite programming language as opposed to squeezing it into a bunch of tables or JSON document. At interacting with the database is handled with a simple set of commands like set followed by a key and value to create data, then get followed by a key to read data. Historically, Redis has been described as a key value store and is often used as a cache to make relational databases faster at scale. But here's where your mind is about to be blown. Redis is perfectly suitable as a primary database, and can dramatically reduce complexity because making things go fast at scale is the primary cause of complexity in the first place. With Redis, your database is already fast. No need for a complex caching layer. But you might be wondering, how do I model complex relationships? Today, Redis is what you would call a multi model database, supporting a variety of different database paradigms with add on modules that you can opt into as needed. If your data contains relationships, at Spring and Redis Graph and query it with Cypher or use the JSON module to structure your data as a hierarchy just like a document in an oriented database, then use the search module to turn your database into a full text search engine, and it even has modules for AI workloads, time series data, and more. The quickest way to get started it is the free tier on Redis enterprise cloud. That'll give you a free database to play around with and you can attach one extra module to it. Then you can connect to it with the Redis CLI or with the Redis Insight tool, which contains an interactive dashboard to manage your data. This has been Redis in 100 seconds. But what do you guys think? Would you use Redis as your primary database? Let me know why or why not in the comments. Thanks for watching, and I will see you in the next one.
Redis,
redis
an
an
in
in
memory
memory
multimodel
multimodel
database
database
famous
famous
for
for
its
its
sub
sub
millisecond
millisecond
latency.
latency
It
it
was
was
created
created
in
in
2009
2009
based
based
on
on
the
the
idea
idea
that
that
a
a
cache
cache
can
can
also
also
be
be
a
a
durable
durable
data
data
store.
store
Around
around
this
this
time,
time
apps
apps
like
like
Twitter
twitter
were
were
growing
growing
exponentially
exponentially
and
and
needed
needed
a
a
way
way
to
to
deliver
deliver
data
data
to
to
their
their
end
end
on
on
users
users
faster
faster
than
than
a
a
relational
relational
database
database
could
could
handle.
handle
Redis,
redis
which
which
means
means
remote
remote
dictionary
dictionary
server,
server
was
was
adopted
adopted
by
by
some
some
of
of
the
the
most
most
heavily
heavily
traffic
traffic
sites
sites
in
in
the
the
world
world
because
because
it
it
changed
changed
the
the
database
database
game
game
by
by
creating
creating
a
a
system
system
where
where
data
data
is
is
always
always
modified
modified
or
or
read
read
from
from
the
the
main
main
computer
computer
memory
memory
as
as
opposed
opposed
to
to
the
the
much
much
slower
slower
disk.
disk
But
but
at
at
the
the
same
same
time,
time
it
it
stores
stores
its
its
data
data
on
on
the
the
disk
disk
so
so
it
it
can
can
be
be
reconstructed
reconstructed
as
as
needed,
needed
which
which
means
means
the
the
database
database
is
is
fully
fully
durable,
durable
supporting
supporting
things
things
like
like
snapshots
snapshots
and
and
backups.
backups
Every
every
data
data
point
point
in
in
the
the
database
database
is
is
a
a
key
key
followed
followed
by
by
one
one
of
of
many
many
different
different
data
data
structures,
structures
like
like
a
a
string,
string
list,
list
hash,
hash
or
or
stream,
stream
so
so
so
so
you
you
can
can
store
store
data
data
naturally
naturally
just
just
like
like
you
you
would
would
with
with
your
your
favorite
favorite
programming
programming
language
language
as
as
opposed
opposed
to
to
squeezing
squeezing
it
it
into
into
a
a
bunch
bunch
of
of
tables
tables
or
or
JSON
json
document.
document
At
at
interacting
interacting
with
with
the
the
database
database
is
is
handled
handled
with
with
a
a
simple
simple
set
set
of
of
commands
commands
like
like
set
set
followed
followed
by
by
a
a
key
key
and
and
value
value
to
to
create
create
data,
data
then
then
get
get
followed
followed
by
by
a
a
key
key
to
to
read
read
data.
data
Historically,
historically
Redis
redis
has
has
been
been
described
described
as
as
a
a
key
key
value
value
store
store
and
and
is
is
often
often
used
used
as
as
a
a
cache
cache
to
to
make
make
relational
relational
databases
databases
faster
faster
at
at
scale.
scale
But
but
here's
here's
where
where
your
your
mind
mind
is
is
about
about
to
to
be
be
blown.
blown
Redis
redis
is
is
perfectly
perfectly
suitable
suitable
as
as
a
a
primary
primary
database,
database
and
and
can
can
dramatically
dramatically
reduce
reduce
complexity
complexity
because
because
making
making
things
things
go
go
fast
fast
at
at
scale
scale
is
is
the
the
primary
primary
cause
cause
of
of
complexity
complexity
in
in
the
the
first
first
place.
place
With
with
Redis,
redis
your
your
database
database
is
is
already
already
fast.
fast
No
no
need
need
for
for
a
a
complex
complex
caching
caching
layer.
layer
But
but
you
you
might
might
be
be
wondering,
wondering
how
how
do
do
I
i
model
model
complex
complex
relationships?
relationships
Today,
today
Redis
redis
is
is
what
what
you
you
would
would
call
call
a
a
multi
multi
model
model
database,
database
supporting
supporting
a
a
variety
variety
of
of
different
different
database
database
paradigms
paradigms
with
with
add
add
on
on
modules
modules
that
that
you
you
can
can
opt
opt
into
into
as
as
needed.
needed
If
if
your
your
data
data
contains
contains
relationships,
relationships
at
at
Spring
spring
and
and
Redis
redis
Graph
graph
and
and
query
query
it
it
with
with
Cypher
cypher
or
or
use
use
the
the
JSON
json
module
module
to
to
structure
structure
your
your
data
data
as
as
a
a
hierarchy
hierarchy
just
just
like
like
a
a
document
document
in
in
an
an
oriented
oriented
database,
database
then
then
use
use
the
the
search
search
module
module
to
to
turn
turn
your
your
database
database
into
into
a
a
full
full
text
text
search
search
engine,
engine
and
and
it
it
even
even
has
has
modules
modules
for
for
AI
ai
workloads,
workloads
time
time
series
series
data,
data
and
and
more.
more
The
the
quickest
quickest
way
way
to
to
get
get
started
started
it
it
is
is
the
the
free
free
tier
tier
on
on
Redis
redis
enterprise
enterprise
cloud.
cloud
That'll
that'll
give
give
you
you
a
a
free
free
database
database
to
to
play
play
around
around
with
with
and
and
you
you
can
can
attach
attach
one
one
extra
extra
module
module
to
to
it.
it
Then
then
you
you
can
can
connect
connect
to
to
it
it
with
with
the
the
Redis
redis
CLI
cli
or
or
with
with
the
the
Redis
redis
Insight
insight
tool,
tool
which
which
contains
contains
an
an
interactive
interactive
dashboard
dashboard
to
to
manage
manage
your
your
data.
data
This
this
has
has
been
been
Redis
redis
in
in
100
100
seconds.
seconds
But
but
what
what
do
do
you
you
guys
guys
think?
think
Would
would
you
you
use
use
Redis
redis
as
as
your
your
primary
primary
database?
database
Let
let
me
me
know
know
why
why
or
or
why
why
not
not
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, a speaker explains how the use of Redis, a multi-mission database, is flexible and fast, allowing for fast access and efficient data transfer. The database is designed to support various types of relationships, including multi-channel, time series data, and more. The speaker also explains how to model relationships and how to use it for AI workloads and time series data.
Redis in 100 Seconds
Redis, an in memory multimodel database famous for its sub millisecond latency. It was created in 2009 based on the idea that a cache can also be a durable data store. Around this time, apps like Twitter were growing exponentially and needed a way to deliver data to their end on users faster than a relational database could handle. Redis, which means remote dictionary server, was adopted by some of the most heavily traffic sites in the world because it changed the database game by creating a system where data is always modified or read from the main computer memory as opposed to the much slower disk. But at the same time, it stores its data on the disk so it can be reconstructed as needed, which means the database is fully durable, supporting things like snapshots and backups. Every data point in the database is a key followed by one of many different data structures, like a string, list, hash, or stream, so so you can store data naturally just like you would with your favorite programming language as opposed to squeezing it into a bunch of tables or JSON document. At interacting with the database is handled with a simple set of commands like set followed by a key and value to create data, then get followed by a key to read data. Historically, Redis has been described as a key value store and is often used as a cache to make relational databases faster at scale. But here's where your mind is about to be blown. Redis is perfectly suitable as a primary database, and can dramatically reduce complexity because making things go fast at scale is the primary cause of complexity in the first place. With Redis, your database is already fast. No need for a complex caching layer. But you might be wondering, how do I model complex relationships? Today, Redis is what you would call a multi model database, supporting a variety of different database paradigms with add on modules that you can opt into as needed. If your data contains relationships, at Spring and Redis Graph and query it with Cypher or use the JSON module to structure your data as a hierarchy just like a document in an oriented database, then use the search module to turn your database into a full text search engine, and it even has modules for AI workloads, time series data, and more. The quickest way to get started it is the free tier on Redis enterprise cloud. That'll give you a free database to play around with and you can attach one extra module to it. Then you can connect to it with the Redis CLI or with the Redis Insight tool, which contains an interactive dashboard to manage your data. This has been Redis in 100 seconds. But what do you guys think? Would you use Redis as your primary database? Let me know why or why not in the comments. Thanks for watching, and I will see you in the next one.
In this video, a speaker explains how the use of Redis, a multi-mission database, is flexible and fast, allowing for fast access and efficient data transfer. The database is designed to support various types of relationships, including multi-channel, time series data, and more. The speaker also explains how to model relationships and how to use it for AI workloads and time series data.

        [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 : Redis in 100 Seconds 
        and a small summary : In this video, a speaker explains how the use of Redis, a multi-mission database, is flexible and fast, allowing for fast access and efficient data transfer. The database is designed to support various types of relationships, including multi-channel, time series data, and more. The speaker also explains how to model relationships and how to use it for AI workloads and time series data.
        [/INST]
        
        Generate the video : Redis, an in memory multimodel database famous for its sub millisecond latency. It was created in 2009 based on the idea that a cache can also be a durable data store. Around this time, apps like Twitter were growing exponentially and needed a way to deliver data to their end on users faster than a relational database could handle. Redis, which means remote dictionary server, was adopted by some of the most heavily traffic sites in the world because it changed the database game by creating a system where data is always modified or read from the main computer memory as opposed to the much slower disk. But at the same time, it stores its data on the disk so it can be reconstructed as needed, which means the database is fully durable, supporting things like snapshots and backups. Every data point in the database is a key followed by one of many different data structures, like a string, list, hash, or stream, so so you can store data naturally just like you would with your favorite programming language as opposed to squeezing it into a bunch of tables or JSON document. At interacting with the database is handled with a simple set of commands like set followed by a key and value to create data, then get followed by a key to read data. Historically, Redis has been described as a key value store and is often used as a cache to make relational databases faster at scale. But here's where your mind is about to be blown. Redis is perfectly suitable as a primary database, and can dramatically reduce complexity because making things go fast at scale is the primary cause of complexity in the first place. With Redis, your database is already fast. No need for a complex caching layer. But you might be wondering, how do I model complex relationships? Today, Redis is what you would call a multi model database, supporting a variety of different database paradigms with add on modules that you can opt into as needed. If your data contains relationships, at Spring and Redis Graph and query it with Cypher or use the JSON module to structure your data as a hierarchy just like a document in an oriented database, then use the search module to turn your database into a full text search engine, and it even has modules for AI workloads, time series data, and more. The quickest way to get started it is the free tier on Redis enterprise cloud. That'll give you a free database to play around with and you can attach one extra module to it. Then you can connect to it with the Redis CLI or with the Redis Insight tool, which contains an interactive dashboard to manage your data. This has been Redis in 100 seconds. But what do you guys think? Would you use Redis as your primary database? Let me know why or why not in the comments. Thanks for watching, and I will see you in the next one.
        