DBMS > KeyDB vs. Lovefield vs. ObjectBox vs. Tkrzw

System Properties Comparison KeyDB vs. Lovefield vs. ObjectBox vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Embeddable relational database for web apps written in pure JavaScript

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Key-value store

Relational DBMS

Object oriented DBMS
Vector DBMS

Key-value store

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

github.com/Snapchat/KeyDB
keydb.dev

google.github.io/lovefield

github.com/objectbox
objectbox.io

dbmx.net/tkrzw

Technical documentation

docs.keydb.dev

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.objectbox.io

Developer

EQ Alpha Technology Ltd.

Google

ObjectBox Limited

Mikio Hirabayashi

Initial release

2019

2014

2017

2020

Current release

2.1.12, February 2017

4.0 (May 2024)

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD-3

Open Source

Apache 2.0

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

JavaScript

C and C++

C++

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

yes, plus "flex" map-like types

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary native API

Supported programming languages

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Lua

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Data sync between devices allowing occasional connected databases to work completely offline

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

using specific database classes

User concepts

Access control

simple password-based access control and ACL

yes

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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More resources

Recent citations in the news

Snap snaps up database developer KeyDB to make its infrastructure more snappy
12 May 2022, TechCrunch

Introducing Garnet – an open-source, next-generation, faster cache-store for accelerating applications and services
18 March 2024, microsoft.com

Microsoft open-sources unique “Garnet” cache-store; a Redis rival?
19 March 2024, The Stack

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2 January 2023, Phoronix

Beyond the mainstream database offerings
26 March 2020, TechCentral.ie

provided by Google News

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