My name is aleksey savateyev i'm program manager for azure
Cosmos db and this is my colleague govind >> yes my name is govind kanshi
We work together on the team and since you have such a big
Crowd we wanted to ensure that you guys get all your questions
Answered today about the so thanks very much for coming
>> Feel free to interrupt us if you think that it were a
Question on whatever we're so we'll do a presentation and
Th let me start first for those
Uninitiated i'm going to give a brief overview of what cosmos
Db really is then we'll talk about [audio difficulties]
For ssively
Scalable database as a service it's built on top of azure
That we are present in 50 plus and whenever new region gets
Introduced we are going to be infrastructure built a resource
Governance resource stack that uses hardware and software to
Power this global distributed low latency database as a
And the critical capabilities of that stack is turnkey global
Can replicate your data to all scale them back whenever you
Storage and throughput that is which is a very cool capability
In contrast to the distributed this on the
And we provide guaranteed low millisecond low latency for
At's for 1 kilobyte documents from a
We also provide five well defined consistency models that
Typically from distributed t strong and
And we also provide we also developed
Different data models on top of that
And it's truly multi modal database because if you think
Ls we model on the other side of the
Spectrum are completely different yet necessity do map
To one set of representation that we call adam record
So key value pair data model is exposed through table api and
You can think of it as a new we also called family deatle
Model that is exposed through cassandra api and govind is
Going to talk to you in detail document is represented by sql
-- It used to be called document db api and the product
Was called doc dd 4 and you might know a product by that
We actually renamed it and smos db
Exactly a year ago during last and another api doc also
Represents document data model mongo api i'm going to talk
And graph data model is exposed through re lynn in api that's
Apache tinker bot nguage to
To govind now who is going to as aleksey said how many people
So you're talking to people who so the key part here is what
Are we doing this and how we and the time limit is a little
Short but we can get into detail as much as
When we get naging
Cassandra how large is a so the key part here is when
You manage large depart systems you are worried about providing
Capacity for throughput as well then you are basically managing
And monitoring a lot of these so what we do is we basically
Basically go ahead and provide sla [audio difficulties]
When we say performance for the
For one kb of data we provide so when we write the data we
Ensure the data is quote uncommitted and indexed all the
And on top of that before i use we also provide the read
For one kb of data again single digit at p 99 percentile you
Don't have to do anything specific for doing any of these
The second important thing here in from normal relational
From the tabases
Managing availability we basically provide within the
You might have seen that we swrus
Introduced a multi master write so you can get far more higher
For our such a
What that simply means is if one agent goes down
Automatically your client applications can move over to
You don't have to do any provide guarantees for the
So when you come to cosmos db as overrun you basically
Request for how many operations experience of yours and move to
An ic based systems you would would need to
In cosmos db we try to make it very easy you just need to tell
Operations reads writes and course
And what we do is we have as he mentioned that we have a
What that implies is that for every operation we take x
Amount of resources and we tell you every time we want i what
That makes is capacity planning is made very easy you know
Of course we also guarantee what that simply means is since
Doesn't mean that we basically share everything with everybody
Whatever you provision is and that is guaranteed
So there is no native interference or
That's the key perspective and so you can basically come back
To us and say i asked for this much throughput and i'm getting
And if you see that anytime it goes up or down you can ask us
>> Then we also provide ability and this throughput you can
If you are working with cassandra or mongo you can of
Course add a machine you have to wait for the machine to be
Be present for the data to be
Present then basically that you don't need to do all of
Decrease the throughput mechanisms we don't put any
Because then you don't have to worry about managing this
Then we also provide you if
Session i think you would have seen we do talk about the
Es in a little bit consistencies normally as you
Might have heard they're strong so majority of the customers
Will either choose stronger eventual but then there are
Customers who require more so on the eventual side we provide consistent prefix which
Is nothing but an audit in the session is client controls
Basically says i [audio difficulties]
We have the boundary says that if the data
Is across x regions they all should be sink in x amount of
Minutes or x amount of time or now one important concept you
Need to get away from the consistency although the title
Is eventual or consistent prefix it doesn't mean the data
Will flow after x amount of g of
Among the data is moved by our data center we don't buffer or
Anything we bush the data the only limitation is speed of
And we provide a matrix for you so this is another important
You can change the consistency quote and push the data so you
Don't choose any consistency you're using cassandra you can
Say okay i want to write just one or you can say
Basically in cassandra you can go ahead and say i want to
Write only one node in our case we always take care that when
Always quote [indiscernible] and on top of that performance
-- So these are the four things
That we provide you all the financial guarantees on and
Then what we do is we also encrypt the data in motion and
And make sure that today we are plan to go improve
That pretty shoon you shuld see so that's i think in very short
Because if you are managing large systems you're worried
About availability you're s you're
Worried about performance we try to take care of all these
Issues that you don't have to so the next one is actually
How cassandra why cassandra very simply why cassandra is
What do you do today with and this is based on the
Customers like you whom we have talked over the years and they
Basically came back when we they basically said if we get
The similar environment where we don't have to manage a
Cassandra cluster or multiple cassandra clusters that would
Pain points are basically jbm managing the cassandra
Yaml the you tuple pairs these are
