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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Cassandra vs Elassandra

Cassandra vs Elassandra

OverviewDecisionsComparisonAlternatives

Overview

Cassandra
Cassandra
Stacks3.6K
Followers3.5K
Votes507
GitHub Stars9.5K
Forks3.8K
Elassandra
Elassandra
Stacks5
Followers36
Votes3

Cassandra vs Elassandra: What are the differences?

Introduction

In the realm of databases, comparing Cassandra to Elassandra reveals key differences that are crucial for users to consider before making a decision. Cassandra is a highly scalable NoSQL database that excels in write-heavy workloads, while Elassandra is a combination of Elasticsearch and Cassandra, offering full-text search capabilities.

  1. Data Model: Cassandra uses a wide column data model, allowing flexible schema design and fast write speeds. In contrast, Elassandra retains the same data model as Cassandra but adds features like full-text search capabilities through integration with Elasticsearch.

  2. Search Capabilities: Elassandra benefits from the search capabilities of Elasticsearch, enabling users to perform complex search queries on their data with ease. On the other hand, Cassandra primarily focuses on providing high availability and fast write performance, with limited search functionality.

  3. Scalability: Both Cassandra and Elassandra are known for their scalability, but Elassandra further enhances this aspect by leveraging Elasticsearch's distributed architecture. This allows Elassandra to handle massive amounts of data while maintaining high performance levels.

  4. Consistency and Availability: Cassandra follows the AP (Availability and Partition Tolerance) design principle, prioritizing high availability and partition tolerance over strong consistency. Elassandra, on the other hand, introduces options for adjusting the consistency level to meet specific requirements, providing more flexibility in balancing consistency and availability.

  5. Community Support: Cassandra has a large and active community, providing extensive resources, documentation, and community support. Elassandra, being a newer project, may have a smaller community base, which could impact the availability of resources and support for users.

  6. Development and Maintenance: Due to the integration of Elasticsearch, Elassandra may require more complex development and maintenance processes compared to Cassandra. Users need to consider the additional resources and expertise needed to manage both Cassandra and Elasticsearch components in an Elassandra deployment.

In Summary, understanding the key differences between Cassandra and Elassandra, such as data model, search capabilities, scalability, consistency, community support, and development complexity, is essential for making an informed decision on selecting the right database solution for specific use cases.

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Advice on Cassandra, Elassandra

Vinay
Vinay

Head of Engineering

Sep 19, 2019

Needs advice

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

174k views174k
Comments

Detailed Comparison

Cassandra
Cassandra
Elassandra
Elassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Elassandra is a fork of Elasticsearch modified to run on top of Apache Cassandra in a scalable and resilient peer-to-peer architecture. Elasticsearch code is embedded in Cassanda nodes providing advanced search features on Cassandra tables and Cassandra serve as an Elasticsearch data and configuration store.

Statistics
GitHub Stars
9.5K
GitHub Stars
-
GitHub Forks
3.8K
GitHub Forks
-
Stacks
3.6K
Stacks
5
Followers
3.5K
Followers
36
Votes
507
Votes
3
Pros & Cons
Pros
  • 119
    Distributed
  • 98
    High performance
  • 81
    High availability
  • 74
    Easy scalability
  • 53
    Replication
Cons
  • 3
    Reliability of replication
  • 1
    Updates
  • 1
    Size
Pros
  • 1
    Multi-master search engine
  • 1
    Well known API
  • 1
    Microservice database and search engine
Integrations
No integrations available
Elasticsearch
Elasticsearch

What are some alternatives to Cassandra, Elassandra?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Algolia

Algolia

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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