Cassandra vs YugabyteDB

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

YugabyteDB

Stacks50

Followers114

Votes1

GitHub Stars9.9K

Forks1.2K

Cassandra vs YugabyteDB: What are the differences?

Cassandra and YugabyteDB are both highly scalable distributed databases that are designed to handle large volumes of data and provide high availability. However, there are several key differences between the two platforms.

Data Model: Cassandra uses a wide-column data model, also known as a column-family data model, where data is organized into rows, columns, and column families. In contrast, YugabyteDB uses a document data model, similar to that of MongoDB, where data is stored as JSON documents.
Consistency Model: Cassandra uses a tunable consistency model, allowing users to choose the desired level of consistency for read and write operations. In contrast, YugabyteDB uses a strongly consistent model by default, ensuring strict consistency across all replicas, but with the option to relax consistency for specific use cases.
Query Language: Cassandra uses CQL (Cassandra Query Language), which is similar to SQL but with some differences and additions to support the wide-column data model. On the other hand, YugabyteDB supports both CQL and SQL, giving users the flexibility to choose the language that best suits their needs.
Multi-Cloud Capability: While both Cassandra and YugabyteDB are cloud-native databases, YugabyteDB is built with multi-cloud architecture in mind. It provides built-in support for running across multiple cloud providers simultaneously, allowing for seamless data replication and high availability across different regions and clouds.
Transaction Support: Cassandra has limited support for transactions and does not natively support ACID transactions. On the other hand, YugabyteDB provides full ACID compliance and supports distributed transactions, making it suitable for applications that require strong consistency guarantees.
Compatibility with PostgreSQL: YugabyteDB is designed to be compatible with PostgreSQL, meaning it supports the PostgreSQL wire protocol and can be used as a drop-in replacement for PostgreSQL. This allows users to leverage existing PostgreSQL tools, libraries, and skills when working with YugabyteDB.

In summary, Cassandra and YugabyteDB differ in their data models, consistency models, query languages, multi-cloud capabilities, transaction support, and compatibility with PostgreSQL. These differences give users a range of options to choose from based on their specific requirements and use cases.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on Cassandra, YugabyteDB

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	YugabyteDB
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.	An open-source, high-performance, distributed SQL database built for resilience and scale. Re-uses the upper half of PostgreSQL to offer advanced RDBMS features, architected to be fully distributed like Google Spanner.
-	Resilience; High Performance; Scalability; Enterprise Grade; Cloud-native; Kubernetes; PostgreSQL-compatible; Geo-Distributed; Hybrid Cloud
Statistics
GitHub Stars 9.5K	GitHub Stars 9.9K
GitHub Forks 3.8K	GitHub Forks 1.2K
Stacks 3.6K	Stacks 50
Followers 3.5K	Followers 114
Votes 507	Votes 1
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 Compatible with the result of pg_dump
Integrations
No integrations available	Golang PHP Java Python Spring Boot Apache Spark Node.js C# Kubernetes Ruby

What are some alternatives to Cassandra, YugabyteDB?

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

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 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.

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 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 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

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 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

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.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Related Comparisons

Cassandra vs YugabyteDB: What are the differences?

Data Model: Cassandra uses a wide-column data model, also known as a column-family data model, where data is organized into rows, columns, and column families. In contrast, YugabyteDB uses a document data model, similar to that of MongoDB, where data is stored as JSON documents.
Consistency Model: Cassandra uses a tunable consistency model, allowing users to choose the desired level of consistency for read and write operations. In contrast, YugabyteDB uses a strongly consistent model by default, ensuring strict consistency across all replicas, but with the option to relax consistency for specific use cases.
Query Language: Cassandra uses CQL (Cassandra Query Language), which is similar to SQL but with some differences and additions to support the wide-column data model. On the other hand, YugabyteDB supports both CQL and SQL, giving users the flexibility to choose the language that best suits their needs.
Multi-Cloud Capability: While both Cassandra and YugabyteDB are cloud-native databases, YugabyteDB is built with multi-cloud architecture in mind. It provides built-in support for running across multiple cloud providers simultaneously, allowing for seamless data replication and high availability across different regions and clouds.
Transaction Support: Cassandra has limited support for transactions and does not natively support ACID transactions. On the other hand, YugabyteDB provides full ACID compliance and supports distributed transactions, making it suitable for applications that require strong consistency guarantees.
Compatibility with PostgreSQL: YugabyteDB is designed to be compatible with PostgreSQL, meaning it supports the PostgreSQL wire protocol and can be used as a drop-in replacement for PostgreSQL. This allows users to leverage existing PostgreSQL tools, libraries, and skills when working with YugabyteDB.

Cassandra vs YugabyteDB

Overview