DBMS > 4D vs. Apache Kylin vs. EJDB vs. RavenDB

System Properties Comparison 4D vs. Apache Kylin vs. EJDB vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

www.4d.com

kylin.apache.org

github.com/Softmotions/ejdb

ravendb.net

Technical documentation

developer.4d.com

kylin.apache.org/docs

github.com/Softmotions/ejdb/blob/master/README.md

ravendb.net/docs

Developer

4D, Inc

Apache Software Foundation, originally contributed from eBay Inc

Softmotions

Hibernating Rhinos

Initial release

1984

2015

2012

2010

Current release

v20, April 2023

3.1.0, July 2020

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2

Open Source

AGPL version 3, commercial license available

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

Server operating systems

OS X
Windows

Linux

server-less

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

ANSI SQL for queries (using Apache Calcite)

SQL-like query language (RQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
RESTful HTTP API

in-process shared library

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Users and groups

Authorization levels configured per client per database

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More resources

DB-Engines blog posts

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2 March 2016, Paul Andlinger

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