Differences 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 System 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 completely 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 is the Top 10 Comparison between the Cassandra vs Elasticsearch
Key Differences Between Cassandra vs Elasticsearch
Below are the lists of points, describe the key Differences Between Cassandra vs Elasticsearch
- Apache Cassandra was developed by Apache Software Foundation which was initially released in the year 2008. Apache Elasticsearch was developed by Elastic and licensed under Apache License 2.0. Cassandra was developed by Shay Banon.
- Cassandra a No SQL database’s main objectives are such as simple design structures, high availability and horizontal scaling, etc. Compared to relational databases, No SQL databases support powerful queries and transactions by following ACID (Atomicity, Consistency, Isolation, and Durability) properties.
- Elasticsearch is a RESTful search that is based on REST (Representational State Transfer) architectural APIs which is highly useful in text-based analysis and filtering of required information from the structured or unstructured data.
- Apache Cassandra is having elastic scalability, fast linear performance, easily distributed architecture, faster queries and transaction support, faster read and write capabilities. It was initially developed at Facebook for searching the messages in Inbox and was made open source later by Facebook. Cassandra has a Query language called CQL which is Cassandra Query language.
- Elasticsearch has numerous applications in the field of data analytics where it can be integrated with multiple tools in terms of data storage and indexing. Indexes can be created and queries can be run in an Elastic search by installing and configuring the Elasticsearch. It is mainly based on the REST API.
- The Apache Cassandra has main 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 be having a powerful indexing search facility with a full-text searching feature.
- Apache Cassandra Node stores data in it and its data centers consist of all the nodes whereas Elasticsearch exposes Java and HTTP APIs in the form of an HTTP GET method to provide searching capability in the form of data retrieval.
- Apache Cassandra cluster is distributed across different machines to handle failures and maintains the replicas to maintain 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 the defines the number of copies of data across different machines to receive multiple copies of data to maintain fault tolerance and high availability whereas Elasticsearch has distributed document storage to power the applications with JSON oriented document platform.
- Apache Cassandra has a facility to add columns whenever or wherever wanted apart from the tradition 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 the Big Data technologies and Dynamo DB database whereas 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 terms of popularity and trending whereas Elasticsearch has more rankings compared to Cassandra.
- Apache Cassandra was initially released in February 2008 whereas Elasticsearch was initially released on April 2008 and both Cassandra and Elasticsearch were written in Java.
- Apache Cassandra supports Linux, OS X, Windows, 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.
Comparison Table between Cassandra vs Elasticsearch
Below are the lists of points, describe the Differences Between Cassandra vs Elasticsearch
| BASIS FOR
COMPARISON |
CASSANDRA |
ELASTICSEARCH |
| License | Open Source No SQL database developed by Apache Open Source Projects | Open source search engine and No SQL database developed by Facebook and made open source |
| Environment | Provided by Apache projects and useful for distributed environments | Cross-platform support and used for a distributed environment. |
| Performance | Provides high scalable and linear performance | High availability and fast index-based searching capability. |
| Scalability | High scalability | Faster query runtimes and high scalability. |
| Pricing | Open Source and depends on the implementation | Open Source and depends on the efficiency of algorithms implemented. |
| Speed | Faster for queries of smaller scripts | Faster due to efficient index searching and storage. |
| Query Speed | Multi Query execution capacity. | Speed queries and transaction capability. |
| Data Integration | Fast and Flexible with different tools. | Support multiple third-party tools to across distributed networks. |
| Data Format | No SQL, SON data formats. | Supports complex data formats such as JSON, NoSQL etc. |
| Ease of Use | Easier to write scripts and queries. | Easier to write queries and transaction as it is REST API based. |
Conclusion – Cassandra vs Elasticsearch
The Apache Cassandra is No SQL based database system and Elasticsearch is a search engine and No SQL based database system, where Elasticsearch is clearly a winner in terms of latest object-oriented or No SQL databases is based on Lucene developed by Apache which is a good index based search engine. In terms of performance scalability and the features, Apache Cassandra can be considered the best database in the case of large amounts of data to be handled.
In most of the cases, Elasticsearch has been the best option for No SQL database system as it is having the added feature of search engine capability compared to the other No SQL database systems in the market.
The advantages of Elasticsearch is that it was based on Apache Lucene which is a data retrieval library completely developed in Java which is a fully featured text-based search engine with high-performance indexing and scalability. This gives much popularity for the Elasticsearch compared to the Cassandra.
4.5 (2,031 ratings)
View Course
Recommended Article
This has been a guide to Difference between Cassandra and Elasticsearch, their Meaning, Head to Head Comparison, Key Differences, Comparison Table, and Conclusion. You may also look at the following articles to learn more –
- Important Points Of C# Interview Questions and Answers
- HBase vs Cassandra – Which One Is Better (Infographics)
- Hadoop vs Elasticsearch – Which one is More Useful
- Supervised Learning vs Unsupervised Learning – Best 7 Useful Comparison
- Java vs Python – Top 9 important Comparisons You Must Learn
- Linux vs OS X
- Groovy Interview Questions: Want to know the best questions
- Go vs Erlang | Features and Comparisons of Go vs Erlang
