DBMS > 4D vs. Datomic vs. DolphinDB vs. Kyligence Enterprise

System Properties Comparison 4D vs. Datomic vs. DolphinDB vs. Kyligence Enterprise

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A distributed analytics engine for big data, built on top of Apache Kylin

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Website

www.4d.com

www.datomic.com

www.dolphindb.com

kyligence.io/kyligence-enterprise

Technical documentation

developer.4d.com

docs.datomic.com

docs.dolphindb.cn/en/help200/index.html

Developer

4D, Inc

Cognitect

DolphinDB, Inc

Kyligence, Inc.

Initial release

1984

2012

2018

2016

Current release

v20, April 2023

1.0.7075, December 2023

v2.00.4, January 2022

License

Commercial or Open Source

commercial

limited edition free

commercial

free community version available

commercial

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, Clojure

C++

Java

Server operating systems

OS X
Windows

All OS with a Java VM

Linux
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

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

SQL-like query language

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
ODBC
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

Clojure
Java

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Users and groups

Administrators, Users, Groups

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More resources

DB-Engines blog posts

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