DBMS > Apache Jena - TDB vs. HEAVY.AI vs. KairosDB vs. Valentina Server

System Properties Comparison Apache Jena - TDB vs. HEAVY.AI vs. KairosDB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Distributed Time Series DBMS based on Cassandra or H2

Object-relational database and reports server

Primary database model

Secondary database models

Spatial DBMS

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

jena.apache.org/documentation/tdb/index.html

github.com/heavyai/heavydb
www.heavy.ai

github.com/kairosdb/kairosdb

www.valentina-db.net

Technical documentation

jena.apache.org/documentation/tdb/index.html

docs.heavy.ai

kairosdb.github.io

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Apache Software Foundation

originally developed by HP Labs

HEAVY.AI, Inc.

Paradigma Software

Initial release

2000

2016

2013

1999

Current release

4.9.0, July 2023

5.10, January 2022

1.2.2, November 2018

5.7.5

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++ and CUDA

Java

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

JDBC
ODBC
Thrift
Vega

Graphite protocol
HTTP REST
Telnet API

ODBC

Supported programming languages

Java

All languages supporting JDBC/ODBC/Thrift
Python

Java
JavaScript

Node.js
PHP
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access control via Jena Security

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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