Cassandra vs Liquibase

Overview

Cassandra

Stacks3.6K

Followers3.5K

Votes507

GitHub Stars9.5K

Forks3.8K

Liquibase

Stacks638

Followers648

Votes70

GitHub Stars5.3K

Forks1.9K

Cassandra vs Liquibase: What are the differences?

Introduction

This Markdown code provides a comparison between Cassandra and Liquibase, highlighting the key differences between the two.

Scalability: Cassandra is a highly scalable and distributed database system, designed to handle large amounts of data across multiple servers. It can easily handle massive amounts of data and provide horizontal scalability. Liquibase, on the other hand, is a database migration tool that helps manage and track changes made to the database schema over time.
Data Model: Cassandra follows a NoSQL data model, specifically a wide-column store, allowing for flexible schemas and dynamic columns. It is suitable for applications that require high availability and low latency. Liquibase, however, is agnostic to the underlying database and works with any database that has a JDBC driver, including both relational and non-relational systems.
Consistency: Cassandra offers eventual consistency, which means that the data may take some time to propagate across all nodes in a distributed cluster. This ensures high availability but sacrifices immediate consistency. Liquibase, on the other hand, focuses on maintaining consistency in the database schema by allowing controlled and repeatable changes.
Data Replication: Cassandra provides built-in support for data replication across multiple nodes, making it highly resilient to failures. It uses a peer-to-peer distributed system with no single point of failure. Liquibase does not have built-in data replication capabilities, as its primary focus is on managing the database schema and tracking changes.
Data Query Language: Cassandra uses CQL (Cassandra Query Language), which is similar to SQL but has additional features specific to Cassandra's data model. It supports complex querying, including filtering, sorting, and aggregating data. Liquibase does not have its own query language, as it primarily operates at the database schema level and uses the SQL queries specific to the underlying database.
Data Integrity: Cassandra provides tunable consistency levels, allowing users to select the desired balance between consistency and availability. It supports the creation of durable writes. Liquibase, on the other hand, focuses on ensuring data integrity through version control and automated database migrations, minimizing human error and providing a history of changes.

In Summary, Cassandra is a scalable and distributed database system optimized for high availability and low latency, while Liquibase is a database migration tool that focuses on managing and tracking changes to the database schema.

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Advice on Cassandra, Liquibase

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	Liquibase
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.	Liquibase is th leading open-source tool for database schema change management. Liquibase helps teams track, version, and deploy database schema and logic changes so they can automate their database code process with their app code process.
-	Supports code branching and merging;Supports multiple developers;Supports multiple database types;Supports XML, YAML, JSON and SQL formats;Supports context-dependent logic;Cluster-safe database upgrades;Generate Database change documentation;Rollbacks;Generate Database "diff's";Run through your build process, embedded in your application or on demand;Automatically generate SQL scripts for DBA code review;Does not require a live database connection;Stored logic
Statistics
GitHub Stars 9.5K	GitHub Stars 5.3K
GitHub Forks 3.8K	GitHub Forks 1.9K
Stacks 3.6K	Stacks 638
Followers 3.5K	Followers 648
Votes 507	Votes 70
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	Pros 18 Great database tool 18 Many DBs supported 12 Easy setup 8 Database independent migration scripts 5 Database version controller Cons 5 No vendor specifics in XML format - needs workarounds 5 Documentation is disorganized
Integrations
No integrations available	Amazon RDS for MariaDB Travis CI SAP HANA Oracle PostgreSQL Sybase jFrog GitHub Actions Firebird IBM DB2

What are some alternatives to Cassandra, Liquibase?

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.

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

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.

dbForge Studio for Oracle

It is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data.

dbForge Studio for PostgreSQL

It is a GUI tool for database development and management. The IDE for PostgreSQL allows users to create, develop, and execute queries, edit and adjust the code to their requirements in a convenient and user-friendly interface.

Related Comparisons

Cassandra vs Liquibase: What are the differences?

Introduction

This Markdown code provides a comparison between Cassandra and Liquibase, highlighting the key differences between the two.

Scalability: Cassandra is a highly scalable and distributed database system, designed to handle large amounts of data across multiple servers. It can easily handle massive amounts of data and provide horizontal scalability. Liquibase, on the other hand, is a database migration tool that helps manage and track changes made to the database schema over time.
Data Model: Cassandra follows a NoSQL data model, specifically a wide-column store, allowing for flexible schemas and dynamic columns. It is suitable for applications that require high availability and low latency. Liquibase, however, is agnostic to the underlying database and works with any database that has a JDBC driver, including both relational and non-relational systems.
Consistency: Cassandra offers eventual consistency, which means that the data may take some time to propagate across all nodes in a distributed cluster. This ensures high availability but sacrifices immediate consistency. Liquibase, on the other hand, focuses on maintaining consistency in the database schema by allowing controlled and repeatable changes.
Data Replication: Cassandra provides built-in support for data replication across multiple nodes, making it highly resilient to failures. It uses a peer-to-peer distributed system with no single point of failure. Liquibase does not have built-in data replication capabilities, as its primary focus is on managing the database schema and tracking changes.
Data Query Language: Cassandra uses CQL (Cassandra Query Language), which is similar to SQL but has additional features specific to Cassandra's data model. It supports complex querying, including filtering, sorting, and aggregating data. Liquibase does not have its own query language, as it primarily operates at the database schema level and uses the SQL queries specific to the underlying database.
Data Integrity: Cassandra provides tunable consistency levels, allowing users to select the desired balance between consistency and availability. It supports the creation of durable writes. Liquibase, on the other hand, focuses on ensuring data integrity through version control and automated database migrations, minimizing human error and providing a history of changes.

Cassandra vs Liquibase

Overview