DBMS > Dgraph vs. IBM Db2 Event Store vs. jBASE vs. RDF4J

System Properties Comparison Dgraph vs. IBM Db2 Event Store vs. jBASE vs. RDF4J

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Distributed Event Store optimized for Internet of Things use cases

A robust multi-value DBMS comprising development tools and middleware

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Graph DBMS

Event Store
Time Series DBMS

Multivalue DBMS

RDF store

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

dgraph.io

www.ibm.com/products/db2-event-store

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

rdf4j.org

Technical documentation

dgraph.io/docs

www.ibm.com/docs/en/db2-event-store

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

rdf4j.org/documentation

Developer

Dgraph Labs, Inc.

IBM

Rocket Software (formerly Zumasys)

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2016

2017

1991

2004

Current release

2.0

5.7

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free developer edition available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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 and C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

AIX
Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

optional

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

through the embedded Spark runtime

Embedded SQL for jBASE in BASIC

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
Basic
Jabbascript
Java

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Active-active shard replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Dgraph on AWS: Setting up a horizontally scalable graph database | Amazon Web Services
1 September 2020, AWS Blog

Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads
26 May 2021, Business Wire

Dgraph launches Slash GraphQL, a GraphQL-native database Backend-as-a-Service
10 September 2020, TechCrunch

Dgraph Raises $6M in Seed Funding
20 July 2022, FinSMEs

provided by Google News

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, IBM

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

Why a robust data management strategy is essential today | IBM HDM
19 September 2019, Express Computer

provided by Google News

Temenos signs first customer in India
24 August 2009, Finextra

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

provided by Google News

Share this page