DBMS > GBase vs. Lovefield vs. OpenEdge vs. Stardog vs. TimesTen

System Properties Comparison GBase vs. Lovefield vs. OpenEdge vs. Stardog vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Embeddable relational database for web apps written in pure JavaScript

Application development environment with integrated database management system

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.gbase.cn

google.github.io/lovefield

www.progress.com/openedge

www.stardog.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

documentation.progress.com/output/ua/OpenEdge_latest

docs.stardog.com

docs.oracle.com/database/timesten-18.1

Developer

General Data Technology Co., Ltd.

Google

Progress Software Corporation

Stardog-Union

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2004

2014

1984

2010

1998

Current release

GBase 8a, GBase 8s, GBase 8c

2.1.12, February 2017

OpenEdge 12.2, March 2020

7.3.0, May 2020

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C, Java, Python

JavaScript

Java

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Windows

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

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

via JavaScript builder pattern

yes

close to SQL 92

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

JavaScript

Progress proprietary ABL (Advanced Business Language)

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and aggregates, HTTP Server extensions in Java

PL/SQL

Triggers

yes

Using read-only observers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

none

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationships in graphs

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

yes

Users and groups

Access rights for users and roles

fine grained access rights according to SQL-standard

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