DBMS > 4D vs. EsgynDB vs. mSQL vs. Splice Machine vs. TerarkDB

System Properties Comparison 4D vs. EsgynDB vs. mSQL vs. Splice Machine vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

mSQL (Mini SQL) is a simple and lightweight RDBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Key-value store

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.4d.com

www.esgyn.cn

hughestech.com.au/products/msql

splicemachine.com

github.com/bytedance/terarkdb

Technical documentation

developer.4d.com

splicemachine.com/how-it-works

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

4D, Inc

Esgyn

Hughes Technologies

Splice Machine

ByteDance, originally Terark

Initial release

1984

2015

1994

2014

2016

Current release

v20, April 2023

4.4, October 2021

3.1, March 2021

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

AGPL 3.0, commercial license available

commercial

restricted open source version 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

C++, Java

Java

C++

Server operating systems

OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
JDBC
ODBC

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

C++ API
Java API

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Delphi
Java
Perl
PHP
Tcl

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C++
Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication between multi datacenters

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

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