DBMS > Raima Database Manager vs. RDF4J vs. Solr vs. WakandaDB

System Properties Comparison Raima Database Manager vs. RDF4J vs. Solr vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

RDBMS with a small footprint, either embedded into an application or used as a database server

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

A widely used distributed, scalable search engine based on Apache Lucene

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS
Time Series DBMS

RDF store

Search engine

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	0.48
Rank	#261	Overall
	#122	Relational DBMS
	#22	Time Series DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	44.28
Rank	#24	Overall
	#3	Search engines

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Website

Technical documentation

docs.raima.com

rdf4j.org/documentation

solr.apache.org/resources.html

wakanda.github.io/doc

Developer

Raima Inc.

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

Apache Software Foundation

Wakanda SAS

Initial release

1984

2004

2006

2012

Current release

15, June 2021

9.5.0, February 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2

Open Source

AGPLv3, extended commercial license available

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

Java

C++, JavaScript

Server operating systems

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

Linux
OS X
Unix
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

Exporting/Importing of XML structures possible

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

.Net
C
C++
Objective-C
PL/SQL

Java
PHP
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

yes

Java plugins

yes

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

yes

More information provided by the system vendor

Specific characteristics

Raima Database Manager (RDM) is an embedded time-series database optimized to run...
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Competitive advantages

Decreased time-to-market Industry-standard interfaces & tools for making your job...
» more

Typical application scenarios

Typical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
» more

Key customers

Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more

Market metrics

Over 30 000 applications developers worldwide have field-tested RDM products More...
» more

Licensing and pricing models

Just as the technical aspects of Raima Database Manager are flexible, so are the...
» more

News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

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

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More resources

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