Cassandra is a Better Option for Handling Big Data in a No-SQL Database
Author
Jyothi J
Abstract
With
no single point of failure and the flexibility to handle enormous volumes of
data across numerous commodity servers, Apache Cassandra is an open-source
distributed database management system. With asynchronous master less
replication, Cassandra provides strong support for clusters spanning several
datacenters and enables low latency operations for all clients. Like skilled
carpenters, data engineers are aware that certain tasks call for various tools.
Choosing the appropriate equipment and being knowledgeable about their use can
be the most crucial aspects of any job. A distributed information system for
managing massive amounts of structured data across multiple goods servers,
Apache Cassandra, a top-level Apache project developed at Facebook and based on
Google's Big Table and Amazon's Generator, offers extremely offered service and
has no single point of failure. In comparison to other NoSQL databases and
relational databases, Cassandra offers features including continuous
availability, linear scale performance, operational simplicity, and
straightforward knowledge distribution over various knowledge centers and cloud
availability zones. Cassandra's capacity to scale, perform, and supply
continuous time period is due to its design. Cassandra uses an attractive,
simple-to-setup, and simple-to-maintain lordless "ring" design rather
than a traditional master-slave or a manual and labor-intensive shared system.
With continuous availability, linear scale performance, operational simplicity,
and simple data distribution over numerous data centers and cloud availability
zones, Apache Cassandra is a massively scalable open-source non-relational
database. Cassandra was initially created at Facebook; it was open sourced in
2008; and in 2010, it was elevated to the status of a top-level Apache project
Keywords
NoSQL database, Cassandra, Column Database, Big Data, Big Data Analytics, RDBMS, and NoSQL
DOI : https://doi.org/10.55248/gengpi.2022.3.9.27
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