DBMS > 4D vs. GridDB vs. H2 vs. LevelDB vs. OrigoDB

System Properties Comparison 4D vs. GridDB vs. H2 vs. LevelDB vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A fully ACID in-memory object graph database

Primary database model

Document store
Object oriented DBMS

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

www.4d.com

griddb.net

www.h2database.com

github.com/google/leveldb

origodb.com

Technical documentation

developer.4d.com

docs.griddb.net

www.h2database.com/html/main.html

github.com/google/leveldb/blob/main/doc/index.md

origodb.com/docs

Developer

4D, Inc

Toshiba Corporation

Thomas Mueller

Google

Robert Friberg et al

Initial release

1984

2013

2005

2011

2009

under the name LiveDB

Current release

v20, April 2023

5.1, August 2022

2.2.220, July 2023

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

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

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD

Open Source

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

C++

Server operating systems

OS X
Windows

Linux

All OS with a Java VM

Illumos
Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

4D proprietary IDE
PHP

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

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

none

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Role based authorization

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

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

Typical application scenarios

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

Key customers

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

Market metrics

GitHub trending repository
» more

Licensing and pricing models

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.

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