
Cassandra Certification Exam
Benefits of LoopSkill Certification

You will become Internationally Certified Cassandra Professional.

Backed by 5000+ Companies this Certification will provide you Great Job Opportunities.

Worldwide Average salary of a Cassandra Professional is around $60,000 per annum.
Exam Cost: USD 30.00




What Is Cassandra?
Apache Cassandra is a distributed, wide-column store, NoSQL database management system that is designed to handle massive volumes of data across many commodity servers while maintaining high availability and avoiding single points of failure. Cassandra supports multi-datacenter clusters, with asynchronous masterless replication allowing all clients to operate with low latency. Cassandra was created to integrate the distributed storage and replication techniques of Amazon's Dynamo with the data and storage engine concept of Google's Bigtable.
Cassandra was created at Facebook by Avinash Lakshman, one of the inventors of Amazon's Dynamo, and Prashant Malik to enable the Facebook inbox search feature. Cassandra was launched as an open-source project on Google code by Facebook in July 2008. It was designated as an Apache Incubator project in March 2009. It was promoted as a top-level project on February 17, 2010. With traditional analogies to a curse on an oracle, Facebook's database was named after the Trojan mythical prophet Cassandra.
Salary Range of A Cassandra Professional
Depending on the experience level and the demographic area, the salary of a Cassandra Professional varies widely.
The following is the average Cassandra Professional Salary in USA:
Best Minds In Cassandra Development | $100,000 |
Senior Cassandra Professionals | $ 85,000 |
Intermediate Cassandra Professionals | $ 65,000 |
Cassandra Fresher | $ 50,000 |
The following is the average Cassandra Professional Salary in India:
Best Minds In Cassandra Development | INR 90,000 |
Senior Cassandra Professionals | INR 60,000 |
Intermediate Cassandra Professionals | INR 35,000 |
Cassandra Fresher | INR 20,000 |
What Is Cassandra Certification?
Cassandra Certification assesses a person's knowledge of the programming language as well as their understanding of database concepts. A variety of certifying authorities, ranging from government agencies to commercial enterprises and organisations, offer the Cassandra certification. Certifications are normally obtained by the completion of an online or offline exam.
All certificates have their own set of benefits, such as international recognition, career opportunities, freelancing, and so on. So, Cassandra certification is an online exam that evaluates a Professional's skills and knowledge in order to match them with the suitable opportunities.
Why should you take this Online Cassandra Certification?
The online Cassandra certification from Loopskill will assist you in becoming a certified Professional. You can take this exam and by scoring 70% you will become an internationally certified Cassandra Professional. This certification will help you in three different ways:
- You can demonstrate your Cassandra certification to potential employers and can stand out of the crowd.
- You can apply for great jobs using loopskill website or app; moreover, our partners companies will contact you directly for full-time or part-time opportunities depending on your skills & requirements.
- Loopskill is not just a platform to get certified or to find full time jobs; here being a certified Professional you can also do freelancing for the clients around the globe. You will be approached by the clients who need your help in building some web based platform or some app based platform.
The loopskill’s online Cassandra certification is created to help people in exploring and achieving their full potential so they can get connected to the best opportunities around the globe.
Main features
Distributed
The role of each node in the cluster is the same. There isn't a single point of failure in this system. Data is dispersed throughout the cluster (so each node has its own set of data), but there is no master because each node can handle any request.
Supports replication and replication across many data centers
Replication strategies can be customized. Cassandra is a distributed system that may be deployed across numerous data centers with a high number of nodes. The distributed architecture of Cassandra is specifically designed for multiple-data-center deployment, redundancy, failover, and disaster recovery.
Scalability
With no downtime or interruption to applications, the read and write throughputs are designed to expand linearly as new computers are added.
Fault-tolerant
For fault tolerance, data is automatically copied to different nodes. It is possible to replicate data across multiple data centers. Nodes that have failed can be replaced without any downtime.
Consistency that can be adjusted
Cassandra is characterized as an AP system, which means that in Cassandra, availability and partition tolerance are seen as more important than consistency. Writes and reads provide a customizable level of consistency, ranging from "never fail writes" to "block for all replicas to be readable," with the quorum level in the center.
Support for MapReduce
Cassandra supports MapReduce and has Hadoop integration. Apache Pig and Apache Hive are also supported.
Language for making queries
The Cassandra Query Language was introduced by Cassandra (CQL). As an alternative to the standard Structured Query Language, CQL is a straightforward interface for querying Cassandra (SQL).
Consistency across time
Cassandra uses Tombstones to manage eventual consistency of reads, upserts, and deletes.
Advantages of Cassandra
Scalability
Cassandra is a character in Cassandra's story. If a system is scalable, your company will not miss out on possibilities during moments of high traffic.
A high level of availability
Cassandra provides high availability by data replication at several locations and across multiple data centers.
The architecture is peer to peer, and it is also masterless, which means that every node can read and write data.
Tolerance to Faults Is Extremely High
When nodes in Cassandra's masterless, peer-to-peer architecture and data replication capabilities are knocked offline, applications never slow down or fail. When a node fails in Cassandra, no manual intervention is required. Because data replicas are available on several nodes in Cassandra, fault tolerance is automatic. If one node goes down, data will be accessible from another node.
High-Efficiency
One of the most important features in Cassandra is high performance. When we talk about high performance, we can state that speed is important. For example, restaurant service, package delivery, and zero lag from our applications.
Support for many data centers and hybrid clouds
Cassandra allows you to connect to various data centers and employ hybrid cloud support. Cassandra is a distributed system that allows huge numbers of nodes to be deployed across many data centers.
Important Topics to Learn & Master in Cassandra
Learning Cassandra will guide you that how to bring your business to the top results to reach your right targeted audience through the free searches.
Cassandra Installation and Configuration
- Course Map
- Objectives
- Cassandra Versions
- Steps to Install and Configure Cassandra on Ubuntu System
- Operating System Selection
- Machine Selection
- Preparing for Installation
- Setup Repository
- Install CassandraCheck the Installation
- Configuring Cassandra
- Configuration for a Single-Node Cluster
- Configuration for a Multi-Node and Multi-Datacenter Clusters
- Setup Property File
- Configuration for a Production Cluster
- Setup Gossiping Property File
- Starting Cassandra Services
- Connecting to Cassandra
- Installing on CentOS
Demo-Installing and Configuring Cassandra on Ubuntu
- Database Design
- Sample Application RDBMS Design
- Sample Application Cassandra Design
- Application Code
- Creating Database
- Loading Schema
- Data Structures
- Setting Connections
- Population of database
- Application Features
Cassandra Data Model
- Advance Modelling
- Rules of Cassandra data modelling
- increasing data writes
- duplication
- reducing data reads
- modelling data around queries
- creating table for data queries
CQL
- Data Definition language(DDL) Statements
- Data Manipulation Language (DML)
- User permission
- Create and modify Users
- Capture CQL output to a file
- Import and export data
- CQL scripts from within CQL
- CQL Scripts from the command prompt
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