The document provides an introduction and overview of NoSQL databases. It discusses why NoSQL databases were created, the different categories of NoSQL databases including column stores, document stores, and key-value stores. It also provides an overview of Hadoop, describing it as a framework that allows distributed processing of large datasets across computer clusters.
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
158ltd.com gives a rapid introduction to NoSQL databases: where they came from, the nature of the data models they use, and the different way you have to think about consistency.
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
158ltd.com gives a rapid introduction to NoSQL databases: where they came from, the nature of the data models they use, and the different way you have to think about consistency.
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 explains why NoSQL databases came over SQL databases although SQL databases has been successfully technology for more than twenty years. Moreover, This presentation discuses the characteristics and classifications of NoSQL databases. Finally, These slides cover four NoSQL databases briefly.
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.
The rising interest in NoSQL technology over the last few years resulted in an increasing number of evaluations and comparisons among competing NoSQL technologies From survey we create a concise and up-to-date comparison of NoSQL engines, identifying their most beneficial use from the software engineer point of view.
NoSQL, as many of you may already know, is basically a database used to manage huge sets of unstructured data, where in the data is not stored in tabular relations like relational databases. Most of the currently existing Relational Databases have failed in solving some of the complex modern problems like:
• Continuously changing nature of data - structured, semi-structured, unstructured and polymorphic data.
• Applications now serve millions of users in different geo-locations, in different timezones and have to be up and running all the time, with data integrity maintained
• Applications are becoming more distributed with many moving towards cloud computing.
NoSQL plays a vital role in an enterprise application which needs to access and analyze a massive set of data that is being made available on multiple virtual servers (remote based) in the cloud infrastructure and mainly when the data set is not structured. Hence, the NoSQL database is designed to overcome the Performance, Scalability, Data Modelling and Distribution limitations that are seen in the Relational Databases.
Can No-SQL technologies hold for the specific requirements that apply to the Telco domain?
This is the Slideshare Presentation by Ericsson Researcher Nicolas Seyvet to accompany his blog "NoSQL for Telco"
http://labs.ericsson.com/blog/nosql-for-telco
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.
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 explains why NoSQL databases came over SQL databases although SQL databases has been successfully technology for more than twenty years. Moreover, This presentation discuses the characteristics and classifications of NoSQL databases. Finally, These slides cover four NoSQL databases briefly.
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.
The rising interest in NoSQL technology over the last few years resulted in an increasing number of evaluations and comparisons among competing NoSQL technologies From survey we create a concise and up-to-date comparison of NoSQL engines, identifying their most beneficial use from the software engineer point of view.
NoSQL, as many of you may already know, is basically a database used to manage huge sets of unstructured data, where in the data is not stored in tabular relations like relational databases. Most of the currently existing Relational Databases have failed in solving some of the complex modern problems like:
• Continuously changing nature of data - structured, semi-structured, unstructured and polymorphic data.
• Applications now serve millions of users in different geo-locations, in different timezones and have to be up and running all the time, with data integrity maintained
• Applications are becoming more distributed with many moving towards cloud computing.
NoSQL plays a vital role in an enterprise application which needs to access and analyze a massive set of data that is being made available on multiple virtual servers (remote based) in the cloud infrastructure and mainly when the data set is not structured. Hence, the NoSQL database is designed to overcome the Performance, Scalability, Data Modelling and Distribution limitations that are seen in the Relational Databases.
Can No-SQL technologies hold for the specific requirements that apply to the Telco domain?
This is the Slideshare Presentation by Ericsson Researcher Nicolas Seyvet to accompany his blog "NoSQL for Telco"
http://labs.ericsson.com/blog/nosql-for-telco
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.
This presentation will helpful for Android Beginner's to refresh the OOPS Concepts which is very basic things for Android Mobile Application Development.
Docker: The basics - Including a demo with an awesome full-stack JS appMarcelo Rodrigues
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What is Jquery, MongoDB and Nashorn?
The high-level architecture of the Online Kanban Board
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DEMO
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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.
Challenges Management and Opportunities of Cloud DBAinventy
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Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
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1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
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Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
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Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
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Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
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https://www.rttsweb.com/jmeter-integration-webinar
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• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
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• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
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DevOps and Testing slides at DASA ConnectKari Kakkonen
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4. Overview of NoSQL (Contd…)
NoSQL doesn’t mean to stop using SQL or SQL won’t be used.
The term refers to those databases that differ from relational databases.
Simply Non-relational databases.
NoSQL is a non-relational database management systems, different from
traditional relational database management systems in some significant ways.
It is designed for distributed data stores where very large scale of data storing
needs (for example Google or Facebook which collects terabits of data every
day for their users). These type of data storing may not require fixed schema,
avoid join operations and typically scale horizontally.
5. NoSQL databases are eventually consistent / CAP (not ACID).
CAP theorem:
Consistency - This means that the data in the database remains consistent
after the execution of an operation. For example after an update operation all
clients see the same data.
Availability - This means that the system is always on (service guarantee
availability), no downtime.
Node failures do not prevent survivors from continuing to operate
Partition Tolerance - This means that the system continues to function even
the communication among the servers is unreliable, i.e. the servers may be
partitioned into multiple groups that cannot communicate with one another.
Overview of NoSQL (Contd…)
6. Overview of NoSQL (Contd…)
NoSQL Features:
1. Scalability
To maintain performance.
Horizontal Scalability:
To increase the number of machines but maintaining proportional
performance.
Vertical scalability:
To add more resources to your single machine to optimize
performance
2. Open Source
Most of the NoSQL Projects are Open source. So any one can use, modify
it, like
Cassandra by facebook.
Bigtable by Google but only allowed for Google application.
7. 3. Schema Freeness
NoSQL databases doesn’t use any fixed schema like relational database.
Internal schema
External schema etc
The original intention of NoSQL is the modern web-scale databases.
There are large number of companies using NoSQL. To name a few :
• Google
• Facebook
• Mozilla
• Adobe
Overview of NoSQL (Contd…)
• Foursquare
• LinkedIn
• Digg
• McGraw-Hill Education
8. WHY NOSQL?
Benefits of NOSQL:
1. Scaling
RDBs weren’t easy to scale out.
On the other hand NoSQL DBs are specially designed to scale out.
2. Big data
Single RDBMS is almost unable to handle today’s huge amount of data and
the transaction on that data.
But
Non-Relational databases are specially designed to handle big data.
Data is becoming easier to capture and access through third parties such as
Facebook, D&B, and others. Personal user information, geo location data,
social graphs, user-generated content, machine logging data, and sensor-
generated data are just a few examples of the ever-expanding array of data
being captured.
3. Needs no Expert DBAs
Although RDMS vendors claim that RDBMS provide management facilities
but it still need an expert DBA to operate it.
In contrast NoSQL DBs don’t need expert DBAs, as it provides automatic
repair, data distribution, and simpler data models, which lead to lower
administration.
9. WHY NOSQL? (CONTD…)
4. Economics
RDBMS requires expensive components for providing efficient service.
NoSQL uses cheap commodity servers to manage the same amount of
data for which RDBMS needs expensive server. So NoSQL is economical
as well.
5. Flexibility of data models
There can occur changes in the requirements of an organization with the
passage of time. Changes in RDBMS after its deployment creates
many problems and also affects its services or some time it’s even almost
impossible to make changes. NoSQL database can be changed at
any instance, i.e. existing columns can be altered and new can be added.
10. WHY NOSQL? (CONTD…)
Scale up with relational technology: limitations at the database tier
Source: http://www.couchbase.com/why-nosql/nosql-database
11. WHY NOSQL? (CONTD…)
Source: http://www.couchbase.com/why-nosql/nosql-database
Scale out with NoSQL technology at the database tier
14. CATEGORIES OF NOSQL DATABASES
There is a variety of types:
• Column Store – Each storage block contains data from only one column
• Document Store – stores documents made up of tagged elements
• Key-Value Store – Hash table of keys
1. Column Store
• Each storage block contains data from only one column
• Example: Hadoop/Hbase
http://hadoop.apache.org/
Clients : Yahoo, Facebook
• Example: Ingres VectorWise
Column Store integrated with an SQL database
• More efficient than row (or document) store if:
Multiple row/record/documents are inserted at the same time so updates of
column blocks can be aggregated
Retrievals access only some of the columns in a row/record/document
15. CATEGORIES OF NOSQL DATABASES (CONTD…)
2. Document Store:
• It stores documents made up of tagged elements.
• Example: CouchDB
http://couchdb.apache.org/
Clients - BBC
• Example: MongoDB
http://www.mongodb.org/
Clients - Foursquare, Shutterfly
16. CATEGORIES OF NOSQL DATABASES (CONTD…)
3. Key-Value Store:
• Hash table of keys
• Values stored with Keys
• Fast access to small data values
• Example – Project-Voldemort
http://www.project-voldemort.com/
Clients : Linkedin
• Example – MemCacheDB
http://memcachedb.org/
17. HADOOP - OVERVIEW
The Apache Hadoop software library is a framework that allows for the distributed
processing of large data sets across clusters of computers using simple
programming models.
It is designed to scale up from single servers to thousands of machines, each
offering local computation and storage.
Rather than rely on hardware to deliver high-availability, the library itself is designed
to detect and handle failures at the application layer, so delivering a highly-available
service on top of a cluster of computers, each of which may be prone to failures.
The Apache Hadoop framework is composed of the following modules :
Hadoop Common - contains libraries and utilities needed by other Hadoop modules
Hadoop Distributed File System (HDFS) - a distributed file-system that stores data
on the commodity machines, providing very high aggregate bandwidth across the
cluster.
Hadoop YARN - a resource-management platform responsible for managing
compute resources in clusters and using them for scheduling of users' applications.
Hadoop MapReduce - a programming model for large scale data processing.