Cassandra vs Elasticsearch

Updated May 4, 2023

Difference Between Cassandra vs Elasticsearch

Apache Cassandra is an open-source and freely distributed No-SQL database management system developed and designed to handle large-scale data across distributed commodity servers. It supports cross-platform Operating Systems Cassandra database provides high availability and zero single points of failure. It also wins in the case of scalability. Apache Elasticsearch is a Search Engine and NoSQL database system based on Apache Lucene Elasticsearch is wholly written using Java programming language. Elasticsearch provides a distributed full-text search engine with schema-less JSON structured documents.

Head-to-Head Comparison Between Cassandra vs Elasticsearch

Below are the top 10 comparisons between Cassandra vs Elasticsearch:

Key Difference Between Cassandra vs Elasticsearch

Below are the lists of points that describe the key Differences Between Cassandra vs Elasticsearch:

• Apache Software Foundation developed Apache Cassandra, which was initially released in 2008. Apache Elasticsearch was developed by Elastic and licensed under Apache License 2.0. Shay Banon developed Cassandra.
• Cassandra, a No SQL database, ’s main objectives are simple design structures, high availability, horizontal scaling, etc. Unlike relational databases, No SQL databases support powerful queries and transactions by following ACID (Atomicity, Consistency, Isolation, and Durability) properties.
• Elasticsearch is a RESTful search based on REST (Representational State Transfer) architectural APIs, which is highly useful in text-based analysis and filtering of required information from structured or unstructured data.
• Apache Cassandra has elastic scalability, fast linear performance, easily distributed architecture, faster queries and transaction support, and faster read and write capabilities. Facebook initially developed it for searching messages in the Inbox and later made it open source. Cassandra has a Query language called CQL which is Cassandra Query language.
• Elasticsearch has numerous applications in data analytics, which can be integrated with multiple data storage and indexing tools. You can create indexes and run queries in Elasticsearch by installing and configuring it. It is mainly based on the REST API.
• Apache Cassandra has core components such as Node, data centers, memory tables, clusters, commit logs, etc., whereas the Cassandra Query Language is used for read-write operations. Elasticsearch is based on Lucene and will have a powerful indexing search facility with a full-text searching feature.
• Apache Cassandra Node stores data and its data centers consist of all the nodes. In contrast, Elasticsearch exposes Java and HTTP APIs as an HTTP GET method to provide searching capability in data retrieval.
• To handle failures, different machines distribute the Apache Cassandra cluster. It maintains the replicas to sustain the operations and transactions with high availability, whereas Elasticsearch works on a Restful distributed search by sending data as documents using the APIs (Application Programming Interfaces).
• Apache Cassandra has a replication factor that defines the number of copies of data across different machines to receive multiple copies of data to maintain fault tolerance and high availability. In contrast, Elasticsearch has distributed document storage to power the applications with JSON oriented document platform.
• Apache Cassandra has the facility to add columns whenever or wherever wanted, apart from the traditional relational-based database systems, whereas Elasticsearch can add data in the form of documents in JSON formats through REST-based APIs.,
• Apache Cassandra deals with unstructured data and has a flexible schema to handle data read-write operations, whereas Elasticsearch deals with JSON-based documented format data.
• Apache Cassandra is a wide column-based storage architecture based on Big Data technologies and a Dynamo DB database. In contrast, Elasticsearch is a distributed and Restful based modern search engine based on Apache Lucene.
• Apache Cassandra scored less in terms of DB engine ranking in popularity and trending, whereas Elasticsearch has more rankings than Cassandra.
• Both Cassandra and Elasticsearch were written in Java, and while Cassandra was initially released in February 2008, Elasticsearch was initially released in April 2008.
• Apache Cassandra supports Linux, OS X, Windows, and BSD Operating Systems, whereas Elasticsearch supports all operating systems with Java Virtual Machine installed.
• Apache Cassandra supports most of the popular object-oriented programming languages such as C#, C++, Java, Go, Erlang, JavaScript, Perl, PHP, Python, Ruby, Scala, etc., whereas Elasticsearch supports.NET, Groovy, Java, JavaScript, Perl, PHP, Python.

Cassandra vs  Elasticsearch Comparison Table

Below are the lists of points that describe the differences Between Cassandra vs Elasticsearch:

Conclusion

Apache Cassandra is No SQL based database system, and Elasticsearch is a search engine and No SQL based database system; Elasticsearch is a winner in terms of the latest object-oriented, or No SQL databases are based on Lucene developed by Apache, which is an excellent index-based search engine. Regarding performance scalability and features, Apache Cassandra can be considered the best database for handling large amounts of data.

In most cases, Elasticsearch has been the best option for a No SQL database system as it has the added feature of search engine capability compared to the other No SQL database systems in the market. The advantage of Elasticsearch is that it was based on Apache Lucene, a data retrieval library wholly developed in Java. It is a fully featured text-based search engine with high-performance indexing and scalability. This gives much popularity for the Elasticsearch compared to Cassandra.

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