Did you ever know how to handle your unstructured data without a single point of failure? The inception of Cassandra has revolutionized the way businesses and enterprises are dealing with the large sets of data exceptionally efficiently and with 100% fault-tolerance.
Apache Cassandra employs to present a scalable, high-available, fault-tolerant database solution for big data processing across multiple servers in organizations. It is yet another Java-based distributed NoSQL DB to handle critical deployments across servers. Cassandra has managed to acquire a good position on the list of NoSQL database market. This, in turn, grows the list of Cassandra adopters in the present big data century.
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Some of the reasons which compelled the technology leaders to deploy Cassandra are:
- Operational simplicity and easy scale out due to master less architecture
- Strong data consistency across distributed cluster
- able to compress up to 80% of the data without any downtime
- Easy transition from relational to NoSQL databases using Cassandra Query Language.
Cassandra versus HBase
Though both the technologies are the open-source projects running the Apache foundation, but both have own advantages and disadvantages. In order to know these a comparative analysis is a must:
|Basis of difference||Cassandra||HBase|
|Foundation||Based on BigTable and DynamoDB||Based on BigTable|
|Read Load Balancing – single Row||Supported||No Supported|
|Language support||More languages supported||Lesser languages supported|
Although, it is easy to find a solution to data processing problems and obstacles, it is difficult to identify a full-proof, no failure system. Cassandra brings us the ultimate key for administering and regulating increasingly expanding data in the world. Together with, Cassandra also serves the purpose of cross-datacenter replication and offer a robust structure along clusters to automatically replicate data between various data nodes.
To help you understand the core functionalities of Cassandra, we have designed this tutorial. It includes Cassandra basics, Data Model, Installation Setup and Configuration steps for beginners, which will also enable intermediate and advanced level professionals to refurbish their basic Cassandra knowledge. Exceeding learner’s expectations and keeping up with the spirit of learning, the tutorial provides insights into Node tool commands, Clusters and Indexes in Cassandra and MapReduce.
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As you go through the tutorial, you will be taken to the next level to write Cassandra Query Language (CQL) and introducing Cassandra Client API. You can also get the overview of Cassandra Architecture and non-relational Cassandra Model. One of the imperative aspects of Cassandra is its tuning performance and this tutorial provides you a detailed summarization of Read and Write operations and Key Cache tuning in Cassandra. The learning language is too interactive for the learners so that they can grasp each topic at a quick pace. CAP Theorem is also well explained in the learning package with the practical implementation of its three faces.
Every technical aspect of Cassandra is mentioned and elaborated here. After finishing this tutorial, you can also explore our Cassandra standalone training and also its combination with other NoSQL database technologies like HBase, MongoDB. The training courses provide 70% of extensive learning through real-time projects, hands-on exercises, assignments and QA.
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- Professionals managing high volumes of data
- Project Managers and working professionals aspiring a career in NoSQL and Cassandra
- IT Developers and Testers who want to expand their dimensions to work with biggest, reputed in organizations
- Big Data Analysts and Architects can gain enrich their big data processing skills through this distributed database management system
- Entry-level and advanced professionals in Java, C++, Python
- Individuals designing Database management projects
- Learning Cassandra requires good understanding of Linux command line basics and Linux Text Editor like VIM, Nano and Emacs.
- Besides, prior knowledge and experience of writing SQL SELECT can help you understand Cassandra concepts easily and quickly.
- You are expected to know Java programming and syntax and data warehousing concepts to keep up your interest during the tutorial.