Introduction to Apache Cassandra
Apache Cassandra is an extremely powerful open-source distributed database system that works really well to handle huge volumes of records spread across multiple commodity servers. It can be easily scaled to meet a sudden increase in demand by deploying multi-node Cassandra clusters and meet high availability requirements, without a single point of failure. It is one of the most efficient NoSQL databases available today. DataStax offers a free packaged distribution of Apache Cassandra. This also includes various other tools such as a Windows Installer, DevCenter, and the DataStax professional documentation.
A NoSQL database is a type of data processing engine that is deployed exclusively for working with data that can be stored in a tabular format and hence does not meet the requirements of relational databases. Some of the salient features of NoSQL databases are that they can handle extremely large amounts of data, can have a simple API, can be replicated easily, are practically schema-free, and are more or less consistent.
NoSQL technologies are designed for being extremely simple, horizontally scalable, and for providing extremely fine control over availability. Data structures used in a NoSQL database are very different from that are used in the relational databases. Due to this, it adds up speed to the operations in NoSQL databases.
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Characteristics of Cassandra
- It is a column-oriented database.
- It is highly consistent, fault-tolerant, and scalable.
- It was created for Facebook and was later open sourced.
- The data model is based on Google Bigtable.
- The distributed design is based on Amazon Dynamo.
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Why should we use Apache Cassandra?
Cassandra is a very robust and complete NoSQL database that is being deployed by some of the biggest corporations on earth such as Facebook, Netflix, Twitter, Cisco, and eBay. The following are some of the obvious features of Cassandra that 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 such as structured, unstructured, and semi-structured data, and it also supports dynamic changes to the data structures to reflect the changing needs.
Linearly Scalable Architecture
It can be easily scaled from a certain set of nodes to a higher set of nodes by a simple addition of extra nodes in a linear fashion without having to get into the complexities, and it gives an immediate increase in the throughput and response time.
This NoSQL database lets you distribute your data in a seamless manner over multiple data centers by a simple process of data replication.
Cassandra is built to handle the failure of nodes in the cluster without affecting the performance in any way as it has no single node failure, an essential feature for mission-critical applications.
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Support for ACID
The properties of ACID (atomicity, consistency, isolation, and durability) are well supported by Cassandra database, which is quite a significant feature since ACID transactions are supported by RDMS.
Go through this short video from Intellipaat elucidating on Cassandra:
High-speed Data Writes
When it comes to the speed of data writing, Cassandra is truly fast and lets you store huge amounts of data on commodity hardware without affecting the read efficiency in any way.
Cassandra NoSQL technology that is so widespread today saw 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 and finally became a part of the Apache top-level project in 2010. Today, it is an integral part of Apache Software Foundation and can be used by anybody interested in benefiting from its multiple uses. The file distribution system in Cassandra is peer-to-peer across the nodes, and due to this all data is distributed across the entire set of nodes in the cluster.
Any node in the cluster can accept the requests for reading or writing data irrespective of whether the data is residing in the cluster or not. The process of how data is replicated 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, and this data is validated for being up-to-date or not. If it is not the latest data, then Cassandra will return with the latest value of the data. The outdated data is then revised with the latest value in order to keep the system updated.
Architecture of Cassandra
Some of the key components of the Cassandra architecture are as follows:
- Cluster: It is a complete set of multiple data centers on which the entire data is stored for processing in the Cassandra NoSQL database.
- Data center: A set of related nodes are grouped in a data center.
- Node: The specific place where the data resides on the cluster is called a node.
- Commit log: It is a failsafe method that is deployed by Cassandra in order to take a backup of all data in the Cassandra database by writing it to the commit log.
- Memtable: It is a data structure that resides in the memory where Cassandra buffers writes. There will be one active Memtable per table.
- SSTable: When Memtables reach their threshold value, they are flushed onto the disk, and they become immutable SSTables.
- Bloom filter: The bloom filter is an algorithm that lets you test whether an element is a member of a set in a swift manner. These bloom filters are accessed after each query.
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 (cqlsh) that allows users to interact with Cassandra.
What is the scope of Apache Cassandra NoSQL tool?
Ever since its open sourcing in 2008, the Cassandra NoSQL tool has found widespread adoption among some of the biggest companies from around the world. Cassandra’s massive decentralized architecture lets these companies store data in a distributed manner while having full control and flexibility in dealing with the data. In addition, no single point of failure makes it irresistible to those organizations that just cannot afford to suffer data loss or server downtime.
Netflix, which is the biggest player in the online streaming of movies and entertainment content, is exclusively using this technology for storing data in a decentralized manner and deploying the replication strategy across its multiple AWS servers to make data more resilient and failsafe.
Cassandra column-oriented data storage methodology makes it quite easy to store data where each row in a column family can contain a varied number of columns, and there is no need for the column names to match. Due to the log-structured storage engine of Cassandra, it is possible to deploy high-speed write operations that are most suited for storing and analyzing sequentially captured metrics.
Owing to its inherent persistent cache of data, Cassandra can be deployed for storing key–value data that needs to have high availability. Due to the linear scalability of Cassandra, there is no downtime as new nodes can be added on demand to the cluster.
Since most of the Big Data available today are in an unstructured format, it makes perfect sense to integrate the NoSQL database Cassandra for Hadoop applications. This is another reason why Cassandra has seen widespread deployment. It is possible to deploy MapReduce jobs read and write operations to the Cassandra database. You can also deploy Apache Pig for querying and storing data in the Cassandra NoSQL database.
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Who is the right audience for learning Apache Cassandra?
- Project Managers and Research and Analytics Professionals
- IT Developers and Testing Professionals
How will learning 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 NoSQL format which could be videos, log data, images, satellite feeds, data from remote sensing, IoT devices, and others. So, it is very vital that professionals deciding upon a career in Hadoop need to understand the NoSQL databases.
This is where the Apache Cassandra NoSQL tool can really help you in taking your career to the next level. Cassandra is a powerful tool that has some unique characteristics, making it one of the best NoSQL tools to integrate into the Hadoop ecosystem. Cassandra is highly effective in working with a whole host of datasets, making it rather a Swiss Army Knife when it comes to processing data. So, qualified Cassandra professionals can really get a staggering hike in their salaries, with increased responsibilities, leading to overall career growth.