Memcached vs WatermelonDB

Overview

Memcached

Stacks7.9K

Followers5.7K

Votes473

GitHub Stars14.0K

Forks3.3K

WatermelonDB

Stacks12

Followers123

Votes1

GitHub Stars11.3K

Forks626

Memcached vs WatermelonDB: What are the differences?

Introduction

In this comparison, we will analyze the key differences between Memcached and WatermelonDB, two popular technologies used for caching and database management in web development.

Data Storage: Memcached is a distributed memory caching system that stores data in the form of key-value pairs in-memory, providing fast access to frequently accessed data. On the other hand, WatermelonDB is a JavaScript library that stores data in a SQLite database, offering a persistent storage solution for web and mobile applications.
Querying Capabilities: Memcached does not support querying capabilities as it mainly focuses on caching and key-based data retrieval. In contrast, WatermelonDB provides robust querying capabilities, allowing developers to perform complex queries and filtering operations on the database.
Data Synchronization: While Memcached does not offer built-in data synchronization mechanisms, WatermelonDB provides synchronization tools that enable real-time data syncing between devices and servers. This feature is particularly useful for applications that require offline access and data consistency.
Data Modeling: Memcached does not require a predefined schema for data storage, simplifying the process of storing and retrieving information. On the other hand, WatermelonDB utilizes a schema-based approach for data modeling, offering more control over the structure and relationships between different data entities.
Concurrency Handling: Memcached does not provide built-in support for handling concurrent data access and modification, making it more suitable for simple caching tasks. In contrast, WatermelonDB incorporates concurrency handling mechanisms to ensure data integrity and consistency in multi-user environments.
Performance Optimization: Memcached is optimized for high-speed data access and is primarily used for caching frequently accessed data to reduce database load. WatermelonDB, on the other hand, focuses on providing a reliable and efficient database management solution with features like background indexing and query optimization for improved performance.

In Summary, Memcached is ideal for caching and fast data retrieval, while WatermelonDB offers a persistent storage solution with advanced querying and synchronization capabilities for web and mobile applications.

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CLI (Node.js)

Manual

Detailed Comparison

Memcached	WatermelonDB
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.	WatermelonDB is a new way of dealing with user data in React Native and React web apps. It's optimized for building complex applications in React Native, and the number one goal is real-world performance. In simple words, your app must launch fast.
Statistics
GitHub Stars 14.0K	GitHub Stars 11.3K
GitHub Forks 3.3K	GitHub Forks 626
Stacks 7.9K	Stacks 12
Followers 5.7K	Followers 123
Votes 473	Votes 1
Pros & Cons
Pros 139 Fast object cache 129 High-performance 91 Stable 65 Mature 33 Distributed caching system Cons 2 Only caches simple types	Pros 1 Undefined is not an object (evaluating 'columnSchema.ty
Integrations
No integrations available	RxJS React SQLite React Native

What are some alternatives to Memcached, WatermelonDB?

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.

Cassandra

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.

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

Memcached vs WatermelonDB: What are the differences?

Introduction

In this comparison, we will analyze the key differences between Memcached and WatermelonDB, two popular technologies used for caching and database management in web development.

Data Storage: Memcached is a distributed memory caching system that stores data in the form of key-value pairs in-memory, providing fast access to frequently accessed data. On the other hand, WatermelonDB is a JavaScript library that stores data in a SQLite database, offering a persistent storage solution for web and mobile applications.
Querying Capabilities: Memcached does not support querying capabilities as it mainly focuses on caching and key-based data retrieval. In contrast, WatermelonDB provides robust querying capabilities, allowing developers to perform complex queries and filtering operations on the database.
Data Synchronization: While Memcached does not offer built-in data synchronization mechanisms, WatermelonDB provides synchronization tools that enable real-time data syncing between devices and servers. This feature is particularly useful for applications that require offline access and data consistency.
Data Modeling: Memcached does not require a predefined schema for data storage, simplifying the process of storing and retrieving information. On the other hand, WatermelonDB utilizes a schema-based approach for data modeling, offering more control over the structure and relationships between different data entities.
Concurrency Handling: Memcached does not provide built-in support for handling concurrent data access and modification, making it more suitable for simple caching tasks. In contrast, WatermelonDB incorporates concurrency handling mechanisms to ensure data integrity and consistency in multi-user environments.
Performance Optimization: Memcached is optimized for high-speed data access and is primarily used for caching frequently accessed data to reduce database load. WatermelonDB, on the other hand, focuses on providing a reliable and efficient database management solution with features like background indexing and query optimization for improved performance.

Memcached vs WatermelonDB

Overview

Memcached vs WatermelonDB: What are the differences?