DBMS > Apache Jena - TDB vs. HugeGraph vs. Quasardb vs. Transwarp Hippo

System Properties Comparison Apache Jena - TDB vs. HugeGraph vs. Quasardb vs. Transwarp Hippo

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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 fast-speed and highly-scalable Graph DBMS

Distributed, high-performance timeseries database

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

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

github.com/hugegraph
hugegraph.apache.org

quasar.ai

www.transwarp.cn/en/subproduct/hippo

Technical documentation

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

hugegraph.apache.org/docs

doc.quasar.ai/master

Developer

Apache Software Foundation

originally developed by HP Labs

Baidu

quasardb

Initial release

2000

2018

2009

2023

Current release

4.9.0, July 2023

0.9

3.14.1, January 2024

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Apache Version 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Java

C++

Server operating systems

All OS with a Java VM

Linux
macOS
Unix

BSD
Linux
OS X
Windows

Linux
macOS

Data scheme

yes

RDF Schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

Vector, Numeric and String

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

also supports composite index and range index

yes

with tags

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API

RESTful HTTP API

Supported programming languages

Java

Groovy
Java
Python

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

C++
Java
Python

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

TDB Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Access control via Jena Security

Users, roles and permissions

Cryptographically strong user authentication and audit trail

Role based access control and fine grained access rights

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