DBMS > 4D vs. EsgynDB vs. Realm vs. TerarkDB vs. Vertica

System Properties Comparison 4D vs. EsgynDB vs. Realm vs. TerarkDB vs. Vertica

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

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	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

www.4d.com

www.esgyn.cn

realm.io

github.com/bytedance/terarkdb

www.vertica.com

Technical documentation

developer.4d.com

realm.io/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

vertica.com/documentation

Developer

4D, Inc

Esgyn

Realm, acquired by MongoDB in May 2019

ByteDance, originally Terark

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1984

2015

2014

2016

2005

Current release

v20, April 2023

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

commercial

restricted open source version available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

C++

Server operating systems

OS X
Windows

Linux

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

close to SQL 92

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
JDBC
ODBC

C++ API
Java API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
Java

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

Java Stored Procedures

runs within the applications so server-side scripts are unnecessary

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Change Listeners

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication between multi datacenters

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

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

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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