DBMS > 4D vs. DuckDB vs. eXtremeDB vs. GridDB vs. RocksDB

System Properties Comparison 4D vs. DuckDB vs. eXtremeDB vs. GridDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Natively in-memory DBMS with options for persistency, high-availability and clustering

Scalable in-memory time series database optimized for IoT and Big Data

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS

Key-value store

Secondary database models

Key-value store
Relational DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

Technical documentation

developer.4d.com

duckdb.org/docs

www.mcobject.com/docs/extremedb.htm

docs.griddb.net

github.com/facebook/rocksdb/wiki

Developer

4D, Inc

McObject

Toshiba Corporation

Facebook, Inc.

Initial release

1984

2018

2001

2013

Current release

v20, April 2023

1.0.0, June 2024

8.2, 2021

5.1, August 2022

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

C++

Server operating systems

OS X
Windows

server-less

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

with the option: eXtremeSQL

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

4D proprietary IDE
PHP

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
C
C#
C++
Java
Lua
Python
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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GitHub trending repository
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.