Both Elasticsearch and Cassandra are NoSQL Databases, which have some similarities, such as NoSQL and open-source databases. Elasticsearch is used for storing unstructured data, and Cassandra is used to handle large volumes of data across the distributed community server.
In the article “Elasticsearch vs Cassandra”, we will discuss what are Elasticsearch and Cassandra with their difference.
Elasticsearch
In the article “Elasticsearch vs Cassandra”, first, we will discuss what Elasticsearch is. Elasticsearch is a NoSQL Database that is basically used to store unstructured data. The unstructured data is stored in Elasticsearch in the document format, which is similar to MongoDB, and the data is serialized in JSON format. There are operations such as create, read, update, and delete, which can be performed on the Elasticsearch database. An example of an Elasticsearch document:
Now in order to understand Elasticsearch vs Cassandra, let's look at the advantages and disadvantages of Elasticsearch in the next subsections.
Advantages of Elasticsearch
Some advantages of Elasticsearch are:-
It stores and operates on unstructured data, which may often change in structure.
To store and operate the data in Elasticsearch is very easy.
As It stores the data in the form of documents, there is flexibility to create nested data easily.
It also works well with the time-series analysis of data.
It is open-source means anyone can use and contribute to Elasticsearch.
Disadvantages of Elasticsearch
Some disadvantages of Elasticsearch are:-
Operating with the data in Elasticsearch can be complex if the user is not familiar with the distributed systems.
The failure scenarios can arise as Elasticsearch can lead to data loss or data inconsistency.
If any failure scenarios arise, problems like data loss or data inconsistency can be led.
The response time and overall performance can be affected if complex queries are used.
Cassandra
In the article “Elasticsearch vs Cassandra”, first, we will discuss what Cassandra is. Cassandra is also a NoSQL Database which is basically used to handle the large-scale data across distributed community servers. Cassandra is an open source that everyone can use and contribute to it. The data in Cassandra is stored in the form of rows and columns.
There are many companies like Google, Facebook, and Netflix which use Cassandra to handle large volumes of data across the distributed community server.
Now in order to understand Elasticsearch vs Cassandra, let's look at the advantages and disadvantages of Cassandra in the next subsections.
Advantages of Cassandra
Some advantages of Cassandra are:-
The large volumes of data can be handled by it.
The performance of data access can be very high as it always delivers low-latency responses.
It provides the balance between data availability and consistency.
Scalability is one of the advantages of Cassandra, as it can easily handle large volumes of data.
Disadvantages of Cassandra
Some disadvantages of Cassandra are:-
It does not provide the ACID (Atomicity, Consistency, Isolation, Durability).
It does not guarantee the transactions.
The problems like storage overhead can arise due to the log-structured storage design.
Performance issues can arise in Cassandra.
There are failure scenarios that can arise as it follows the eventual consistency model.
Difference between Elasticsearch and Cassandra
In the article “Elasticsearch vs Cassandra”, we will discuss the difference between Elasticsearch and Cassandra:
Basis
Elasticsearch
Cassandra
Definition
It is a NoSQL Database that is basically used to store unstructured data. The unstructured data is stored in Elasticsearch in the document format.
It is also a NoSQL Database which is basically used to handle the large-scale data across distributed community servers.
Developed By
It was developed by Facebook in 2010.
It is developed by Apache Open Source Projects in 2008.
Speed
Index searching makes the speed of Elasticsearch faster.
The speed of Cassandra is faster for the queries of small scripts.
Language Support
There are various languages, such as Java, Perl, PHP, and Python, that are supported by it.
There are various languages, such as Go, Java, Ruby, Scala, and Python, that are supported by it.
Performance
Fast performance can be achieved by using index searching in it.
There is a linear performance in it.
Scalability
It provides high scalability and faster query runtime.
It also provides high scalability, as it can easily handle large volumes of data.
Frequently Asked Questions
Why to use Elasticsearch?
Elasticsearch is easy to store and operate the data. As Elasticsearch stores the data in the form of documents, there is flexibility to create nested data easily. It is an open-source means anyone can use and contribute to Elasticsearch.
Why to use Cassandra?
Cassandra can be used to handle large-scale data across distributed community servers. The performance of data access can be very high as Cassandra delivers low-latency responses.
Does Cassandra provide ACID property for transactions?
Cassandra does not provide the ACID (Atomicity, Consistency, Isolation, Durability), which does not guarantee that transactions and storage overhead can arise due to the log-structured storage design.
Can Elasticsearch replace Cassandra or vice versa?
Yes, both Elasticsearch and Cassandra can be replaced with each other. Like if the use case is search and operations, then Elasticsearch can replace Cassandra. If the use case is high throughput, then Cassandra can replace Elasticsearch.
Conclusion
We have seen both Elasticsearch and Cassandra are NoSQL databases that have some points in common, like NoSQL and open-source. In the article “Elasticsearch vs Cassandra”, we discussed what are the Elasticsearch and Cassandra with their advantages and disadvantages. We also discussed the differences between Elasticsearch and Cassandra.
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