DBMS > Firebird vs. Manticore Search vs. Newts vs. RDF4J vs. TimesTen

System Properties Comparison Firebird vs. Manticore Search vs. Newts vs. RDF4J vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Firebird is an open source RDBMS forked from Borland's InterBase

Multi-storage database for search, including full-text search.

Time Series DBMS based on Cassandra

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.firebirdsql.org

manticoresearch.com

opennms.github.io/newts

rdf4j.org

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

Technical documentation

www.firebirdsql.org/en/reference-manuals

manual.manticoresearch.com

github.com/OpenNMS/newts/wiki

rdf4j.org/documentation

docs.oracle.com/database/timesten-18.1

Developer

Firebird Foundation

Manticore Software

OpenNMS Group

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

Oracle, TimesTen Performance Software, HP

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

Initial release

2000

As fork of Borland's InterBase

2017

2014

2004

1998

Current release

5.0.0, January 2024

6.0, February 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Initial Developer's Public License

Open Source

GPL version 2

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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 and C++

C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

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

Data scheme

yes

Fixed schema

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

HTTP REST
Java API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java

Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

PSQL

user defined functions

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication based on Galera library

selectable replication factor

based on Cassandra

none

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

in-memory storage is supported as well

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

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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