KeyDB vs MapDB

Overview

MapDB

Stacks8

Followers49

Votes0

KeyDB

Stacks37

Followers62

Votes5

KeyDB vs MapDB: What are the differences?

In-Memory Database vs. On-Disk Database: One key difference between KeyDB and MapDB is that KeyDB is an in-memory database, while MapDB is an on-disk database. This means that KeyDB is optimized for fast data access and retrieval as it stores data in memory, while MapDB is designed for persistent storage on disk.
Concurrency Control: Another difference is that KeyDB offers built-in support for thread-safe concurrency control mechanisms, such as Multi-Version Concurrency Control (MVCC) and fine-grained locking. On the other hand, MapDB does not provide built-in support for concurrency control, and developers need to implement their own strategies for managing concurrent access to the data.
Supported Data Structures: KeyDB focuses on supporting key-value data structures and operations, similar to Redis, making it ideal for caching and real-time data processing applications. In contrast, MapDB is more versatile and supports various data structures, such as B-trees, Hash tables, and AVL trees, making it suitable for a wider range of use cases beyond key-value stores.
Community and Support: KeyDB has a growing community of users and developers who actively contribute to its development and provide support through forums and documentation. MapDB also has a supportive community, but it may not be as extensive as KeyDB's community.
Programming Language: KeyDB is primarily written in C and C++, which offers high performance and low-level system access. On the other hand, MapDB is implemented in Java, which allows for platform independence and ease of use for developers familiar with the Java programming language.
License: KeyDB is released under the open-source BSD 2-Clause License, which allows for commercial use and modification of the code without significant restrictions. In contrast, MapDB is licensed under the Apache License 2.0, which also permits commercial use but has different requirements regarding patent rights and trademark use.

In Summary, KeyDB and MapDB differ in their in-memory vs. on-disk storage, concurrency control mechanisms, supported data structures, community support, programming languages, and licensing.

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

Detailed Comparison

MapDB	KeyDB
MapDB provides Java Maps, Sets, Lists, Queues and other collections backed by off-heap or on-disk storage. It is a hybrid between java collection framework and embedded database engine. It is free and open-source under Apache license.	KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity.
Concurrency; Writing database; Code duplication and not invented here; Does not integrate with default tools and defacto standards; Did not follow test driven development; Not enough performance testing. ...	Active Replication; FLASH storage support; direct backup to AWS S3; MultiMaster; Multithreaded
Statistics
Stacks 8	Stacks 37
Followers 49	Followers 62
Votes 0	Votes 5
Pros & Cons
No community feedback yet	Pros 3 Performance 2 Active Replication
Integrations
Presto Clever Cloud SignalFx Datadog OpsDash Actionhero	No integrations available

What are some alternatives to MapDB, KeyDB?

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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.

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.

dbForge Studio for SQL Server

It is a powerful IDE for SQL Server management, administration, development, data reporting and analysis. The tool will help SQL developers to manage databases, version-control database changes in popular source control systems, speed up routine tasks, as well, as to make complex database changes.

Liquibase

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.

Sequel Pro

Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases.

DBeaver

It is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, Teradata, MongoDB, Cassandra, Redis, etc.

dbForge SQL Complete

It is an IntelliSense add-in for SQL Server Management Studio, designed to provide the fastest T-SQL query typing ever possible.

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Related Comparisons

KeyDB vs MapDB: What are the differences?

In-Memory Database vs. On-Disk Database: One key difference between KeyDB and MapDB is that KeyDB is an in-memory database, while MapDB is an on-disk database. This means that KeyDB is optimized for fast data access and retrieval as it stores data in memory, while MapDB is designed for persistent storage on disk.
Concurrency Control: Another difference is that KeyDB offers built-in support for thread-safe concurrency control mechanisms, such as Multi-Version Concurrency Control (MVCC) and fine-grained locking. On the other hand, MapDB does not provide built-in support for concurrency control, and developers need to implement their own strategies for managing concurrent access to the data.
Supported Data Structures: KeyDB focuses on supporting key-value data structures and operations, similar to Redis, making it ideal for caching and real-time data processing applications. In contrast, MapDB is more versatile and supports various data structures, such as B-trees, Hash tables, and AVL trees, making it suitable for a wider range of use cases beyond key-value stores.
Community and Support: KeyDB has a growing community of users and developers who actively contribute to its development and provide support through forums and documentation. MapDB also has a supportive community, but it may not be as extensive as KeyDB's community.
Programming Language: KeyDB is primarily written in C and C++, which offers high performance and low-level system access. On the other hand, MapDB is implemented in Java, which allows for platform independence and ease of use for developers familiar with the Java programming language.
License: KeyDB is released under the open-source BSD 2-Clause License, which allows for commercial use and modification of the code without significant restrictions. In contrast, MapDB is licensed under the Apache License 2.0, which also permits commercial use but has different requirements regarding patent rights and trademark use.

In Summary, KeyDB and MapDB differ in their in-memory vs. on-disk storage, concurrency control mechanisms, supported data structures, community support, programming languages, and licensing.

KeyDB vs MapDB

Overview