DBMS > 4D vs. LeanXcale vs. XTDB

System Properties Comparison 4D vs. LeanXcale vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

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

Score	2.68
Rank	#110	Overall
	#54	Relational DBMS

Score	0.35
Rank	#283	Overall
	#41	Key-value stores
	#128	Relational DBMS

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

www.4d.com

www.leanxcale.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

developer.4d.com

www.xtdb.com/docs

Developer

4D, Inc

LeanXcale

Juxt Ltd.

Initial release

1984

2015

2019

Current release

v20, April 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Clojure

Server operating systems

OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL

Support of SQL

yes

close to SQL 92

yes

through Apache Derby

limited SQL, making use of Apache Calcite

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST
JDBC

Supported programming languages

4D proprietary IDE
PHP

C
Java
Scala

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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More resources

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