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NoSQL Data Management Technologies was designed to meet the big data requirements when databases like MySQL and Oracle failed in scaling for large data volumes. Big data refers to a large amount of data that has volume, velocity, and variety. Volume refers to the amount of data, velocity refers to the generation speed, and variety denotes the data type. NoSQL came into existence when relational databases proved non-effective to store a huge amount of data.
What is a NoSQL database?
Today every organization working on big data emphasizes the importance of data management with NoSQL. NoSQL databases are known as “Not Only SQL” which means that they also support SQL-like query language but do not have a fixed table structure and are based on a flexible schema. NoSQL databases are more scalable and offer better performance compared to relational databases. NoSQL can do a lot more than a relational database. It is capable of running on a high number of nodes because of its scale-out architecture. It has a non-locking concurrency control mechanism that allows real-time reads to not conflict with writes. It supports data distribution across thousands of machines and does not stick to a particular schema. NoSQL can be further classified into a wide range of different technologies. But, the choices bring confusion. Well, sit back and let us compare the widely used NoSQL database- Cassandra, MongoDB, and Hbase for you.
Apache Cassandra is one NoSQL database that is written in java. It was originally developed by Facebook to handle their inbox search feature. Cassandra database does not need the matching of a column with a row. Apache Cassandra provides high availability and is consistent. Cassandra has a decentralized structure where any node can respond to requests, thus enabling it to avoid single node failure.
Some of the features and advantages of Apache Cassandra are:
- Apache works with a wide column store.
- AP on CAP
- Cassandra performs fast reads and writes.
- No multiple secondary indexes are required in Apache Cassandra
Apache Cassandra’s disadvantages:
- When the architecture is distributed, replicas may become inconsistent.
- When scanning day, it suffers when the primary key is not known.
- Another drawback of Cassandra is the aggregation. They must be provided by the clients.
Hbase database is an open-source distributed system that provides scalability and fault tolerance. Hbase is built over HDFS (Hadoop Distributed File System) and supports real-time analytics. It also offers a freestanding kind of its database which helps in many development configurations.
Key features and advantages of the Hbase database:
- It works with a documented oriented database and data is stored as key or values.
- Hbase is well suited for range based scan and provides seamless scalability.
- Hbase supports Bigtable, Bloom filters and block caches that play a vital role in optimizing the queries.
- Hbase includes tables, however, a schema is only required for tables and not for columns.
- Hbase is written in a custom language that needs to be learned for running queries.
- HBase is somewhat similar to Cassandra but has different architectures.
- Hbase works on a typical master-slave architecture and takes a lot of time while failing from one HMaster to another. This results in single-point failure.
- Since Hbase does not have a query language one is bound to use the JRuby-based Hbase shell to achieve the capabilities of SQL.
- Hbase is highly dependent on HDFS and Its hardware requirements are extremely high.
MongoDB is one of the most famous open-source database systems. It offers both community and enterprise versions. MongoDB was created in 2007 to address the issues of internet ads. It has a structured document query mechanism and is often used to store large data files, such as images and videos.
Key Features and Advantages of MongoDB:
- MongoDB works on a schema-less database that goes over tear bytes of data.
- It provides full index support for high performances.
- MongoDB stores data in JSON/Binary JSON-like documents.
- It works on real-time analytics and offers high-speed logging and scalability.
- MongoDB uses master-slave replication architecture and integrates data much faster.
- It offers CP from CAP theorem and features auto sharding for easy scalability.
- MongoDB is not good for a highly transactional system.
- It does not work well for applications with traditional database requirements like foreign key constraints.
- MongoDB also suffers from memory hog issues.
MongoDB is the most popular database among all the NoSql databases. But, if you are someone who is looking for a system that is always available, then Apache Cassandra is a better choice. With so many NoSQL databases available, the tough choice is to decide on one
Ksolves has emerged as the best Apache Cassandra Development company in the market. If you are still confused and wonder which NoSQL suits your business the best, Reach out to us.
Email : firstname.lastname@example.org
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Read related articles:
Advantages of NoSQL over RDBMS: Is the Former a Clear Winner?
Apache Cassandra Vs MySQL- What Should You Use & Why?
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One thought on “Cassandra vs. MongoDB vs. Hbase: A Comparison of NoSQL Databases”
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