Elasticsearch vs Cassandra

Both Elasticsearch and Cassandra are NoSQL databases. Elasticsearch is a database search engine developed by Facebook, and Cassandra is a NoSQL database management system developed by Apache Open Source Projects. Elasticsearch is used to store the unstructured data, while Cassandra is designed to handle a large amount of data across the distributed community server. Both databases are open-source, so the users don't need to pay anything to use them.

However, Elasticsearch and Cassandra have some similarities like the NoSQL database and open-source products, but they also have some differences that make them different from each other. First, we will discuss briefly about Elasticsearch and Apache Cassandra separately and then their differences. Below is a list of differences of Elasticsearch and Cassandra.

Elasticsearch

Elasticsearch is an open-source NoSQL database tool that can be easily deployed and operated. It is used for the analytic purpose and searching your logs and data in general. Basically, it is a NoSQL database to store the unstructured data in the document format.

Remember that Elasticsearch can perform all three analysis, visualization and search operations on data only by integrating with Logstash and Kibana tools. The integration of Elasticsearch with Logstash and Kibana is known as ELK stack.

Cassandra

Apache Cassandra is a NoSQL database management system that belongs to the database category. It is developed by Apache Open Source Projects to handle the large-scale data across distributed community servers. It was released in 2008. It is an open-source that offers easy scalability and zero points of failure.

Cassandra manages the data in rows and columns. It runs on JVM (Java Virtual Machine). Several popular companies like Spotify, Facebook, Netflix, Uber technologies, etc. use Apache Cassandra to handle their data across the distribute server.

Difference between Elasticsearch and Cassandra

Elasticsearch and Cassandra both have several similarities but also have some differences. Based on some parameters, we will discuss their differences in detail. A list of differences is given below:

Comparison parameters	Elasticsearch	Cassandra
License	Elasticsearch is developed by Facebook to store unstructured data in document form	Cassandra is developed by Apache Open Source Projects.
Speed	Efficient index searching makes the Elasticsearch faster.	Cassandra is faster for the queries of small script.
Integration with	Elasticsearch tool integrates with Logstash and Kibana for a complete ELK stack. Apart from that, it can also integrate with various other tools, such as - Datadog, Couchbase, Amazon Elasticsearch Services, and Contentful, etc.	Apache Cassandra can also integrate with several other tools like Datadog, Presto, Buddy, Kong, and Redash, etc.
Cost	As we already discussed, it is an open-source tool. So, users don't need to pay anything.	Like the Elasticsearch, Apache Cassandra is also a free tool.
Dependency	Elasticsearch is dependent on the efficiency of algorithm's implementation.	Cassandra depends on implementation.
Language support	Several languages like Java, .NET, Perl, Groovy, PHP, and Python are supported by Elasticsearch.	Cassandra also provides support to many languages, such as Erlang, Ruby, Scala, Go, Java, and Python, etc. Mostly, it supports object-oriented programming languages.
Ease of use	As Elasticsearch is REST API based, so it is easy to write queries and transactions.	In Apache Cassandra, it is easy to write queries and script.
Performance	Elasticsearch offers high availability, and it also has the capability of fast index-based searching, which improves its performance.	On the other side, Apache Cassandra offers linear performance.
Scalability	Along with the above features, it also provides high scalability and faster query runtime.	High scalability is also an important feature of Cassandra which defines that it is highly scalable.
Companies used	Several companies like Uber, Stack Overflow, Udemy, Shopify, Instacart, and Slank, etc. use ElasticStack to store, analyze, search, and visualize their data. Where Elasticsearch, Logstash, and Kibana perform their role very sharply.	On the other hand, Cassandra is also used by a number of companies like Spotify, Facebook, Netflix, Uber technologies, etc.

Conclusion

In the end, come to the conclusion that which one is better Elasticsearch or Cassandra. Both are excellent tools for storing data. Apart from that, if we compare both of them, no doubt Elasticsearch is winner in terms of the latest object-oriented. As it's a NoSQL database which is based on Lucene that offers an excellent index-based search engine. This is an advantage of Elasticsearch.

For the NoSQL database, Elasticsearch has been the best option as it includes another excellent feature that is search engine capability.

Wherever based on some other features like performance and scalability, Apache Cassandra can also be taken into consideration that it is best database when it comes to handling large amounts of data.

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