This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
This presentation contains the introduction to NOSQL databases, it's types with examples, differentiation with 40 year old relational database management system, it's usage, why and we should use it.
“not only SQL.”
NoSQL databases are databases store data in a format other than relational tables.
NoSQL databases or non-relational databases don’t store relationship data well.
This presentation explains the major differences between SQL and NoSQL databases in terms of Scalability, Flexibility and Performance. It also talks about MongoDB which is a document-based NoSQL database and explains the database strutre for my mouse-human research classifier project.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
This presentation covers the following topics:
1. HBase versions and origins
2. HBase core concepts
3. HBase vs. RDBMS
4. Data Modeling
5. HBase architecture
6. HBase Master and Region Servers
7. Column Families and Regions
8. HBase Internals: Bloom Filters and Block Indexes
9. Write Pipeline / Read Pipeline
10. Compactions
11. Learning Resources
This presentation is all about for the difference in between the Sql and NoSQL database because this question generally comes in the mind of every people that on what parameters and
how we can differentiate both these databases.
So, after viewing this presentation all your doubts and misconfusion between Sql and NoSQL got clear.
Apache HBase™ is the Hadoop database, a distributed, salable, big data store.Its a column-oriented database management system that runs on top of HDFS.
Apache HBase is an open source NoSQL database that provides real-time read/write access to those large data sets. ... HBase is natively integrated with Hadoop and works seamlessly alongside other data access engines through YARN.
Modern databases and its challenges (SQL ,NoSQL, NewSQL)Mohamed Galal
Nowadays the amount of data becomes very large, every organization produces a huge amount of data daily.
Thus we want new technology to help in storing and query a huge amount of data in acceptable time.
The old relational model may help in consistency but it was not designed to deal with big data problem.
In this slides, I will describe the relational model, NoSql Models and the NewSql models with some examples.
This presentation contains the introduction to NOSQL databases, it's types with examples, differentiation with 40 year old relational database management system, it's usage, why and we should use it.
“not only SQL.”
NoSQL databases are databases store data in a format other than relational tables.
NoSQL databases or non-relational databases don’t store relationship data well.
This presentation explains the major differences between SQL and NoSQL databases in terms of Scalability, Flexibility and Performance. It also talks about MongoDB which is a document-based NoSQL database and explains the database strutre for my mouse-human research classifier project.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
This presentation covers the following topics:
1. HBase versions and origins
2. HBase core concepts
3. HBase vs. RDBMS
4. Data Modeling
5. HBase architecture
6. HBase Master and Region Servers
7. Column Families and Regions
8. HBase Internals: Bloom Filters and Block Indexes
9. Write Pipeline / Read Pipeline
10. Compactions
11. Learning Resources
This presentation is all about for the difference in between the Sql and NoSQL database because this question generally comes in the mind of every people that on what parameters and
how we can differentiate both these databases.
So, after viewing this presentation all your doubts and misconfusion between Sql and NoSQL got clear.
Apache HBase™ is the Hadoop database, a distributed, salable, big data store.Its a column-oriented database management system that runs on top of HDFS.
Apache HBase is an open source NoSQL database that provides real-time read/write access to those large data sets. ... HBase is natively integrated with Hadoop and works seamlessly alongside other data access engines through YARN.
Modern databases and its challenges (SQL ,NoSQL, NewSQL)Mohamed Galal
Nowadays the amount of data becomes very large, every organization produces a huge amount of data daily.
Thus we want new technology to help in storing and query a huge amount of data in acceptable time.
The old relational model may help in consistency but it was not designed to deal with big data problem.
In this slides, I will describe the relational model, NoSql Models and the NewSql models with some examples.
What is NoSQL? How does it come to the picture? What are the types of NoSQL? Some basics of different NoSQL types? Differences between RDBMS and NoSQL. Pros and Cons of NoSQL.
What is MongoDB? What are the features of MongoDB? Nexus architecture of MongoDB. Data model and query model of MongoDB? Various MongoDB data management techniques. Indexing in MongoDB. A working example using MongoDB Java driver on Mac OSX.
Presentation on NoSQL Database related RDBMSabdurrobsoyon
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
في الفيديو ده بيتم شرح ما هي المشاكل التي انتجت ظهور هذا النوع من قواعد البيانات
انواع المشاريع التي يمكن استخدامها بها
نبذة عن تاريخها و مزاياها و عيوبها
https://youtu.be/I9zgrdCf0fY
Enterprise NoSQL: Silver Bullet or Poison PillBilly Newport
This is a slightly revised version of the keynote I gave for the first time at StrangeLoop 2010. It tries to shows the pros and cons of NoSQL versus SQL and highlight whats easy and not so easy to do so people have a better understanding of typical NoSQL type products.
Here is my seminar presentation on No-SQL Databases. it includes all the types of nosql databases, merits & demerits of nosql databases, examples of nosql databases etc.
For seminar report of NoSQL Databases please contact me: ndc@live.in
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This is a MUG with a twist you don't want to miss.
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1. An introduction to
NoSQL databases
POOYAN MEHRPARVAR
DEC 2014To get more references visit:
http://bit.ly/nosql_srbiau
1
2. What is covered in this
presentation:
A brief history of data bases
NoSQL why, what and when?
Aggregate Data Models
BASE vs ACID
CAP theorem
Polyglot persistence : the future of database systems
2
3. Why did we choose this topic?
Is NoSQL replacing traditional databases?
Where should we use NoSQL databases?
Should we use NoSQL in any kind of projects?
3
5. Relational databases
Benefits of Relational databases:
Designed for all purposes
ACID
Strong consistancy, concurrency,
recovery
Mathematical background
Standard Query language (SQL)
Lots of tools to use with i.e: Reporting
services, entity frameworks, ...
Vertical scaling (up scaling)
Object / Object-relational databases
were not practical. Mainly because of
Impedance mismatch
5
6. Era of Distributed Computing
But...
Relational databases were not built for
distributed applications.
Because...
Joins are expensive
Hard to scale horizontally
Impedance mismatch occurs
Expensive (product cost, hardware,
Maintenance)
6
7. Era of Distributed Computing
But...
Relational databases were not built for
distributed applications.
Because...
Joins are expensive
Hard to scale horizontally
Impedance mismatch occurs
Expensive (product cost, hardware,
Maintenance)
And....
It’s weak in:
Speed (performance)
High availability
Partition tolerance
7
8. Rise of Big data
Three V(s) of Bigdata:
Volume
Velocity
Variety
8
10. Rise of Big data
Wallmart: 1 million transactions per
hour
Facebook: 40 billion photos
People are talking about petabytes
today
10
11. NoSQL why, what and when?
Google & Amazon bulit their own databases (Big table & Dynamo)
Facebook invented Cassandra and is using thousands of them
#NoSQL was a twitter hashtag for a conference in 2009
The name doesn’t indicate its characteristics
There is no strict defenition for NoSQL databases
There are more than 150 NoSQL databases (nosql-database.org)
11
12. Characteristics of NoSQL databases
Non relational
Cluster friendly
Schema-less
21 century web
Open-source
12
13. Characteristics of NoSQL databases
NoSQL avoids:
Overhead of ACID transactions
Complexity of SQL query
Burden of up-front schema design
DBA presence
Transactions (It should be handled at
application layer)
Provides:
Easy and frequent changes to DB
Horizontal scaling (scaling out)
Solution to Impedance mismatch
Fast development
13
15. What is a schema-less datamodel?
In relational Databases:
You can’t add a record which does not fit
the schema
You need to add NULLs to unused items in
a row
We should consider the datatypes. i.e :
you can’t add a stirng to an interger field
You can’t add multiple items in a field
(You should create another table:
primary-key, foreign key, joins,
normalization, ... !!!)
15
16. What is a schema-less datamodel?
In NoSQL Databases:
There is no schema to consider
There is no unused cell
There is no datatype (implicit)
Most of considerations are done in
application layer
We gather all items in an aggregate
(document)
16
17. What is Aggregation?
The term comes from Domain Driven Design
Shared nothing architecture
An aggregate is a cluster of domain objects that can be treated as
a single unit
Aggregates are the basic element of transfer of data storage - you
request to load or save whole aggregates
Transactions should not cross aggregate boundaries
This mechanism reduces the join operations to a minimal level
17
21. Aggregate Data Models
NoSQL databases are classified in four major datamodels:
Key-value
Document
Column family
Graph
Each DB has its own query language
21
22. Key-value data model
The main idea is the use of a hash table
Access data (values) by strings called keys
Data has no required format – data may have any format
Data model: (key, value) pairs
Basic Operations:
Insert(key,value), Fetch(key),Update(key), Delete(key)
22
23. Key-value data model
“Value” is stored as a “blob”
- Without caring or knowing what is inside
- Application is responsible for understanding the
data
Main observation from Amazon (using Dynamo)
– “There are many services on Amazon’s platform
that only need primary-key access to a data
store.”
E.g. Best seller lists, shopping carts, customer
preferences, session management, sales rank,
product catalog
23
24. Column family data model
The column is lowest/smallest instance of
data.
It is a tuple that contains a name, a value
and a timestamp
24
25. Column family data model
Some statistics about Facebook Search (using Cassandra)
MySQL > 50 GB Data
Writes Average : ~300 ms
Reads Average : ~350 ms
Rewritten with Cassandra > 50 GB Data
Writes Average : 0.12 ms
Reads Average : 15 ms
25
26. Graph data model
Based on Graph Theory.
Scale vertically, no clustering.
You can use graph algorithms easily
Transactions
ACID
26
27. Document-based datamodel
Usually JSON like interchange model.
Query Model: JavaScript-like or custom.
Aggregations: Map/Reduce
Indexes are done via B-Trees.
unlike simple key-value stores, both keys
and values are fully searchable in
document databases.
27
33. A sample MongoDB query 33
MySQL:
MongoDB:
There is no join in MongoDB query
Because we are using an aggregate data model
34. What we need?
We need a distributed database system having such
features:
– Fault tolerance
– High availability
– Consistency
– Scalability
34
35. What we need?
We need a distributed database system having such
features:
– Fault tolerance
– High availability
– Consistency
– Scalability
Which is impossible!!!
According to CAP theorem
35
36. Should we...?
In some cases getting an answer quickly is
more important than getting a correct
answer
By giving up ACID properties, one can
achieve higher performance and scalability.
Any data store can achieve Atomicity,
Isolation and Durability but do you always
need consistency?
Maybe we should implement Asynchronous
Inserts and updates and should not wait for
confirmation?
36
37. BASE
Almost the opposite of ACID.
Basically available: Nodes in the a distributed
environment can go down, but the whole
system shouldn’t be affected.
Soft State (scalable): The state of the system and
data changes over time.
Eventual Consistency: Given enough time, data
will be consistent across the distributed system.
37
39. CAP theorem
Consistency: Clients should
read the same data. There
are many levels of
consistency.
o Strict Consistency – RDBMS.
o Tunable Consistency –
Cassandra.
o Eventual Consistency –
Mongodb.
Availability: Data to be
available.
Partial Tolerance: Data to
be partitioned across
network segments due to
network failures.
39
40. CAP theorem in different SQL/NoSQL
databases
We can not achieve all the three items
In distributed database systems (center) Proven by Nancy Lynch et al. MIT labs.
40
45. Polyglot persistence : the future of database
systems
Future databases are the combination of SQL & NoSQL
We still need relational databases
45
47. New approach to database systems:
Integrated databases has its own
advantages and disadvantages
With the advent of webservices it
seems now it’s the time to switch
to decentralized data bases
Single point of failure, Bottlenecks
would be avoided
Clustering & replication would be
much easier
47
48. Conclusion:
Before you choose NoSQL as a solution:
Consider these items, ...
Needs a precise evaluation, Maybe NoSQL is not the right thing
Needs to read lots of case study papers
Aggregation is totally a different approach
NoSQL is still immature
Needs lots of hours of studing and working to expert in a particular
NoSQL db
There is no standard query language
Most of controls have to be implemented at the application layer
Relational databases are still the strongest in transactional environments
and provide the best solutions in consistancy and concurrency control
48
51. NewSQL a brief defenition
NewSQL group was founded in 2011
Michael Stonebraker’s Definition …
SQL as the primary interface.
ACID support for transactions
Non-locking concurrency control.
High per-node performance.
Parallel, shared-nothing architecture – each node is
independent and self-sufficient – do not share memory or storage
51
52. Technology is still in its infancy...
In 2000 no one even thought database
systems could be a hot topic again!
To get more references visit:
http://bit.ly/nosql_srbiau
52
Who is familiar with NoSQL?
Who has worked with a practical distributed database?
First of all you have to forgot about the SQL view. NoSQL is a kind of new approach
A friend chose Mongodb as a solution for their log db.
But it faild because they have some difficulties about transactions. (there is no transaction)
Maybe it’s due to their lack of knowlage about NoSQL dbs
Partitioning and Memcache in RDMSs
Scale up is expensive – we need to scale out
We have acid transactions in graph databases
We have atomicity in an aggregate (a document in MongoDB)
Facebook is using +6000 cassandra dbs.
Have you seen the same with oracle or db2 (RDMS are suitable to upscaling)
That’s how google extend its clusters everyday.
Good for social networks & CS projects
Mongodb has auto sharding, map/reduce module
-> As the data is written, the latest version is on at least one node. The data is then versioned/replicated to other nodes within the system.
-> Eventually, the same version is on all nodes.
For a given accepted update and a given node, eventually either the update reaches the node or the node is removed from service
Consistency (all nodes see the same data at the same time)
Availability (a guarantee that every request receives a response about whether it succeeded or failed)
Partition tolerance (the system continues to operate despite arbitrary message loss or failure of part of the system)
In nosql we prefer Avaibility.
When there is a inconsistancy in shoping, the most important thing is to shop!! (Amazon’s example)
A RDMS will do such a thing. The whole system will be down until it comes to a consistant level
We choose between C & A (it’s not a binary decision)
It depends on our domain to decide about the inconsistency window (we should talk to the domain experts)
Distribution methods: replication (master-slave, peer to peer) and sharding. Cassandra uses sharding and peer to peer
Master-slave (single point of failure – good in consistency)
Peer to peer (consistency is expensive)
Replica sets are used for data redundancy, automated failover, read scaling, server maintenance without downtime.
An idea for the thesis:
Test nosql (e.g. mongodb) ability to scale out with virtual machines (various Lubuntu machines)
Dental clinic example – xml as a solution – nosql as solution
Facebook query example : show me a female < 30 who is intested in y music living in z
Most of projects have some custom tables