Big data is revolutionizing the world of the IT industry, and according to Forbes, analysts estimate upward of 80% of enterprise data is unstructured. Unstructured data cannot always be handled in real-time if an organization tries to store this data and their DBMS, it will be difficult to scale up the data in real-time to get better performance. Here we are discussing Cassandra vs. MongoDB vs. HBase. First, we need to understand what a NoSQL database is.
NoSQL, which stands for “Not Only SQL,” is an alternative to a traditional relational database. Data is placed in a table, and the data schema is carefully designed before the database is built.
Why need No SQL database?
As compared to relational databases, NoSQL is more scalable and provides superior performance. NoSQL databases provide the following solutions such as:
- Capable of running on a larger number of nodes.
- More scalable and provide superior performance.
- It also provides a non-locking concurrency mechanism.
- It can scale and replicate thousands of machines with distributed data.
- The architecture of no sequel database provides a higher performance node than a DBMS and has a schema-less data model.
Cassandra vs. MongoDB vs. HBase
Types of NoSQL Database
There are four types of databases such as:
It has a big hash table of keys, and values, for example, Amazon S3.
Column Based Store
In this case, each storage block contains data from only one column, like Cassandra and HBase.
It stores the document that is made up of tag elements, for example, CouchDB or MongoDB.
In this case, a network database uses edges and knows to represent and store the data, for example, Neo4j.
Apache Cassandra is the leading no-sequel distributed data management system that drives many of today’s modern business applications by offering continuous availability, high scalability, performance, strong security, and operational simplicity by lowering the overall cost of ownership.
Data Model of Cassandra
Cassandra is a white-column store model based on the ideas of BigTable and the dynamo database. Moreover, it consists of keyspaces, the outer container in Cassandra, and the column family contains an ordered collection of rows.
Cassandra’s implementation can implement by using one of the most popular object-oriented programming languages called Java.
Cassandra uses its query language Called Cassandra query language.
- TLS/SSL Encryption
- Client Authentication
It is a documented-oriented database. All the data in MongoDB is traded in JSON format, and it is a schema-less database that goes over terabytes of data in the database.
Data Model of MongoDB
MongoDB is a document storage architecture with data. MongoDB also has a flexible schema document in the collection. It doesn’t need to have the same set of structure fields, but common fields in the collections document may hold different types of data.
MongoDB can implement using C++ programming language through these databases’ implementation using object-oriented concepts. It also provides wide support to all other programming languages.
Apache HBase is a no sequel key-value store which runs at the top of HDFS. Unlike high HBase, operations run in real-time on its database rather than the Map Reduce jobs.
Data Model of Apache HBase
Column Oriented Database
It is partitioned into tables, and tables are future split into column families. Column families must be declared in the schema and grouped by a certain set of columns so that columns don’t require schema definition, and HBase works by storing data like keys and values.
Cassandra is implemented by using one of the most popular object-oriented programming languages called Java.
HBase uses the query language MapReduce.
- Thrift server role.
Author: SVCIT Editorial
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