DBMS > 4D vs. H2 vs. KeyDB vs. LeanXcale vs. ObjectBox

System Properties Comparison 4D vs. H2 vs. KeyDB vs. LeanXcale vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Primary database model

Relational DBMS

Key-value store

Key-value store
Relational DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

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

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

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

Website

www.4d.com

www.h2database.com

github.com/Snapchat/KeyDB
keydb.dev

www.leanxcale.com

github.com/objectbox
objectbox.io

Technical documentation

developer.4d.com

www.h2database.com/html/main.html

docs.keydb.dev

docs.objectbox.io

Developer

4D, Inc

Thomas Mueller

EQ Alpha Technology Ltd.

LeanXcale

ObjectBox Limited

Initial release

1984

2005

2019

2015

2017

Current release

v20, April 2023

2.2.220, July 2023

4.0 (May 2024)

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD-3

commercial

Bindings are released under Apache 2.0

Apache License 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

Java

C++

C and C++

Server operating systems

OS X
Windows

All OS with a Java VM

Linux

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

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

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.

yes

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

close to SQL 92

yes

through Apache Derby

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Proprietary native API

Supported programming languages

4D proprietary IDE
PHP

Java

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

C
Java
Scala

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

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

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