Cassandra vs Vitess

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

Vitess

Stacks66

Followers166

Votes0

Cassandra vs Vitess: What are the differences?

Introduction: When comparing Cassandra and Vitess, it becomes evident that each database system has its own unique features and functionalities that cater to specific use cases and requirements. Understanding the key differences between Cassandra and Vitess can help in making informed decisions regarding database selection for various applications.

Data Model: Cassandra is a wide-column NoSQL database that utilizes tables, rows, and columns for data storage. It supports flexible schema design, allowing columns to vary for each row. On the other hand, Vitess is a horizontal scaling system for MySQL databases, enabling sharding of tables to distribute data across multiple instances. It maintains the relational data model of MySQL, providing SQL-like query capabilities.
Consistency Model: Cassandra employs tunable consistency levels, allowing users to balance consistency and availability based on their requirements. It offers a choice between strong and eventual consistency. In contrast, Vitess operates under a strict serializable isolation level, ensuring strong consistency across sharded data. This approach simplifies data integrity but may impact availability under certain conditions.
Distribution Strategy: Cassandra relies on a peer-to-peer distributed architecture, where each node can accept read and write requests independently. It utilizes consistent hashing to determine data placement on nodes, ensuring data distribution and fault tolerance. Vitess, on the other hand, employs a master-slave replication model where writes are forwarded to the master node for processing. This centralized approach simplifies data consistency but can create bottlenecks during high write loads.
Query Language Support: Cassandra uses the Cassandra Query Language (CQL), which is a close variant of SQL optimized for distributed data management. It supports basic CRUD operations and secondary indexing. In contrast, Vitess supports standard SQL queries, enabling seamless integration with existing MySQL applications. It provides additional features such as query rewriting and routing to enhance performance and scalability.
Use Cases: Cassandra is well-suited for applications requiring high availability, fault tolerance, and linear scalability. It is commonly used in scenarios involving time-series data, real-time analytics, and content management systems. On the other hand, Vitess is ideal for scaling-out MySQL databases without sacrificing ACID compliance. It is commonly employed in e-commerce platforms, online gaming, and other transactional systems that demand strong consistency and seamless sharding capabilities.
Community Support and Ecosystem: Cassandra has a vibrant open-source community with extensive documentation, forums, and third-party tools available for developers. It offers a wide range of drivers and integrations for various programming languages and frameworks. In comparison, Vitess is primarily supported by the Vitess community, which provides detailed documentation and resources for deploying and managing the system. It offers integrations with Kubernetes for containerized deployments and orchestration.

In Summary, understanding the key differences between Cassandra and Vitess in terms of data model, consistency model, distribution strategy, query language support, use cases, and community support can aid in selecting the appropriate database system for specific application requirements.

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Advice on Cassandra, Vitess

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.

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Comments

Detailed Comparison

Cassandra	Vitess
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.	It is a database solution for deploying, scaling and managing large clusters of MySQL instances. It’s architected to run as effectively in a public or private cloud architecture as it does on dedicated hardware. It combines and extends many important MySQL features with the scalability of a NoSQL database.
-	Scalability; Connection pooling; Manageability
Statistics
GitHub Stars 9.5K	GitHub Stars -
GitHub Forks 3.8K	GitHub Forks -
Stacks 3.6K	Stacks 66
Followers 3.5K	Followers 166
Votes 507	Votes 0
Pros & Cons
Pros 119 Distributed 98 High performance 81 High availability 74 Easy scalability 53 Replication Cons 3 Reliability of replication 1 Size 1 Updates	No community feedback yet
Integrations
No integrations available	Amazon RDS Kubernetes MySQL

What are some alternatives to Cassandra, Vitess?

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 Vitess: What are the differences?

Data Model: Cassandra is a wide-column NoSQL database that utilizes tables, rows, and columns for data storage. It supports flexible schema design, allowing columns to vary for each row. On the other hand, Vitess is a horizontal scaling system for MySQL databases, enabling sharding of tables to distribute data across multiple instances. It maintains the relational data model of MySQL, providing SQL-like query capabilities.
Consistency Model: Cassandra employs tunable consistency levels, allowing users to balance consistency and availability based on their requirements. It offers a choice between strong and eventual consistency. In contrast, Vitess operates under a strict serializable isolation level, ensuring strong consistency across sharded data. This approach simplifies data integrity but may impact availability under certain conditions.
Distribution Strategy: Cassandra relies on a peer-to-peer distributed architecture, where each node can accept read and write requests independently. It utilizes consistent hashing to determine data placement on nodes, ensuring data distribution and fault tolerance. Vitess, on the other hand, employs a master-slave replication model where writes are forwarded to the master node for processing. This centralized approach simplifies data consistency but can create bottlenecks during high write loads.
Query Language Support: Cassandra uses the Cassandra Query Language (CQL), which is a close variant of SQL optimized for distributed data management. It supports basic CRUD operations and secondary indexing. In contrast, Vitess supports standard SQL queries, enabling seamless integration with existing MySQL applications. It provides additional features such as query rewriting and routing to enhance performance and scalability.
Use Cases: Cassandra is well-suited for applications requiring high availability, fault tolerance, and linear scalability. It is commonly used in scenarios involving time-series data, real-time analytics, and content management systems. On the other hand, Vitess is ideal for scaling-out MySQL databases without sacrificing ACID compliance. It is commonly employed in e-commerce platforms, online gaming, and other transactional systems that demand strong consistency and seamless sharding capabilities.
Community Support and Ecosystem: Cassandra has a vibrant open-source community with extensive documentation, forums, and third-party tools available for developers. It offers a wide range of drivers and integrations for various programming languages and frameworks. In comparison, Vitess is primarily supported by the Vitess community, which provides detailed documentation and resources for deploying and managing the system. It offers integrations with Kubernetes for containerized deployments and orchestration.

Cassandra vs Vitess

Overview