Apache Cassandra is a highly scalable. Also, it is one of the available distributed databases. It will facilitate the storing. Also, managing high velocity of the structured data. This will be across the multiple commodity servers. It is possible without a single point of the failure.
Introduction to Apache Cassandra:
It is an extremely powerful open-source distributed DB system. This is to handle huge volumes of records. These records were widely in the multiple commodity servers. We can easily scale it. This is to meet a sudden increase in demand. It is possible by deploying multi-node Cassandra clusters. Also, we can meet high available requirements. We can achieve this without a single point of failure. It is one of the most efficient No-SQL databases. It is available in today’s market. Data-Stax offers a free packaged distribution of Apache Cassandra. It will also include various other tools. Some of them are as follows. They are,
Windows Installer.
Dev Center.
Data Stax professional documentation.
A No-SQL database is a type of data processing engine. It can deploy exclusively for working with data. Also, it can store in a tabular format. Hence, it does not meet the requirements of relational databases. Following are some of the salient features of No-SQL databases.
They can handle extremely large amounts of data.
They can have a simple API.
It can replicate easily.
Practically schema-free.
They are consistent.
They design the No-SQL technologies extremely for the following. They are,
Simple.
Horizontally scalable.
Providing extremely fine control over availability.
Data structures used in a No-SQL database are very different. They are used to the relational databases. Due to this, it adds up speed to the operations in No-SQL databases.
Characteristics of Cassandra:
Following are some of the Characteristics of Cassandra. They are,
It is a column-oriented database.
It is a highly consistent, fault tolerant as well as scalable.
They created this for Facebook as well as it was later becoming an open sourced.
The data model will base on Google Big table.
The distributed design will base on Amazon Dynamo.
Why should we use Apache Cassandra?
Cassandra is a very robust and complete No-SQL database. It can deploy by some of the biggest corporations. Following are some of them. They are,
Facebook.
Netflix.
Twitter.
Cisco.
eBay.
The following are some of the obvious features of Cassandra. It will clearly make it stand out from the crowd.
Support for a Wide Set of Data Structures:
Cassandra lets you support data structures of all kinds. It means it will support structured, unstructured, and semi-structured data. Also, it will support dynamic changes to the data structures. These changes will reflect as the needed change.
Linearly Scalable Architecture:
We can easily scale from a certain set of nodes. This is to a higher set of nodes. This is possible by a simple addition of extra nodes. It will be in a linear fashion. This is without having to get into the complexities. Also, it gives an immediate increase in the throughput and response time.
Seamless Distribution:
This No-SQL database lets you distribute your data. This will be in the seamless manner. It is over multiple data centers. This is possible by a simple process of data replication.
High Reliability:
Cassandra is built to handle the failure of nodes in the cluster. This is without affecting the performance in any way. It has no single node failure. So, it has an essential feature for mission-critical apps.
Support for ACID:
The properties of ACID are well supported by Cassandra database. It is a quite significant feature. Since, the RDMS support the ACID transactions.
High-speed Data Writes:
When we consider the speed of data writing, then Cassandra is truly fast. Also, let you store huge amounts of data on commodity hardware. This is possible without affecting the read efficiency in any way.
Cassandra No-SQL technology is so widespread today. You can able to see its genesis in the Facebook inbox search. The social media giant open sourced Cassandra in July 2008. It became a part of Apache Incubator in 2009. Also, finally became a part of the Apache top-level project in 2010. Today, it is an integral part of Apache Software Foundation. Also, anybody with interest can use this. This will be the benefit for its multiple uses. The file distribution system in Cr-to-peer will be across the nodes. This is the reason for all data distributed across the entire set of nodes in the cluster.
Any node in the cluster can accept the requests. Especially for the reading or writing data. This will be irrespective of whether the data is residing in the cluster or not. The process of how data will replicate in Cassandra is via some of the nodes. That act as replicas for a certain chunk of data. Today, there is a large amount of data. Also, this data will validate for being up to date or not. If it is not the latest data, then Cassandra will return with the latest value. The outdated data is then revised with the latest value. This will be in order to keep the system updated.
Architecture of Cassandra:
Following are some of the key components of the Cassandra architecture. They are,
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Cluster: It is a complete set of multiple data centers. Especially on which the entire data will store for processing in the Cassandra No-SQL database.
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Data center: Simply we can call a set of related nodes as grouped in a data center.
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Node: Similarly, we can call the specific place where the data resides on the cluster as node.
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Commit log: It is a fail-safe method. We can deploy by Cassandra. This will be in order to take a backup of all data in the Cassandra database. This is possible by writing it to the commit log.
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Memtable: It is a data structure that resides in the memory where Cassandra buffers writes. There will be one active Memtable per table.
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SSTable: When Memtables reach their threshold value, they will flush onto the disk. Then they become immutable SSTables.
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Bloom filter: The bloom filter is an algorithm allows you to test. Whether an element is a member of a set in a swift manner or not? These bloom filters are accessed after each query.
Understanding CQL:
CQL stands for the Cassandra query language. CQL lets you access the Cassandra database through its node. This query language treats the database as a container of tables. This query language also provides a prompt Cassandra query language shell. It will allow the users to interact with Cassandra.
What is the scope of Apache Cassandra No-SQL tool?
The Cassandra No-SQL tool has found widespread adoption. This will be among some of the biggest companies from around the world. Cassandra’s massive decentralized architecture allows these companies to store the data. This will be in a distributed manner. While having full control and flexible in dealing with the data. Also, no single point of failure makes it irresistible to those industry. It just cannot afford to suffer data loss or server downtime.
Netflix is the biggest player in the online streaming of movies. Also, in the entertainment content. It is exclusively using this technology for storing the data. This will be in a decentralized manner. Also, deploying the replication strategy across its multiple AWS servers. This is to make data more resilient and fail-safe.
Cassandra column-oriented data is a storage methodology. This will make it quite easy. It is to store data where each row in a column family. It can contain a varied number of columns. Also, there is no need for the column names to match. Due to the log-structured storage engine of Cassandra, it is possible to deploy. Especially for the high-speed write operations. These are most suited for storing as well as analyzing sequentially captured metrics.
Owing to its inherent persistent cache of data. Cassandra can deploy for storing key–value data that needs to have high availability. Due to the linear scalability of Cassandra, there is no downtime. We can add any new nodes which will be on demand to the cluster.
Most of the Big Data available today are in an unstructured format. It makes perfect sense to integrate the No-SQL database Cassandra for Hadoop apps. This is another reason why Cassandra has seen widespread deployment. It is possible to deploy Map Reduce jobs read and write operations to the Cassandra database. You can also deploy Apache Pig for querying. Also, you can store the data in the Cassandra No-SQL database.
Who is the right audience for learning Apache Cassandra?
Project Managers and Research and Analytics Experts.
IT Developers and Testing Experts.
How will learning the Apache Cassandra help you in your career?
Today, the whole world is revolving around Big Data and Hadoop. It is a fact that most of the big data comes in the No-SQL format. It may be in the following formats.
Videos.
Log data.
Images.
Satellite feeds.
Data from remote sensing.
IoT devices, and others.
So, it is very vital that experts deciding upon a career in Hadoop. It needs to understand the No-SQL databases.
This is where the Apache Cassandra No-SQL tool can really help you. Especially in taking your career to the next level. Cassandra is a powerful tool. It has some unique characteristics. This will make it as one of the best No-SQL tools. Especially, to integrate into the Hadoop ecosystem. Cassandra is highly effective in working with a whole host of data sets. This will make it rather a Swiss Army Knife when it comes to processing data. So, qualified Cassandra experts can really get a staggering hike in their salaries. This is possible with increased responsibilities. This will lead to the overall career growth.
