DBMS > Hive vs. Hyprcubd vs. RDF4J vs. SwayDB vs. TerminusDB

System Properties Comparison Hive vs. Hyprcubd vs. RDF4J vs. SwayDB vs. TerminusDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Serverless Time Series DBMS

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store
RDF store

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

hive.apache.org

hyprcubd.com (offline)

rdf4j.org

swaydb.simer.au

terminusdb.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

rdf4j.org/documentation

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

initially developed by Facebook

Hyprcubd, Inc.

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

Simer Plaha

DataChemist Ltd.

Initial release

2012

2004

2018

Current release

3.1.3, April 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GNU Affero GPL V3.0

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

Prolog, Rust

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

RDF Schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

SQL-like DML and DDL statements

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
Thrift

gRPC (https)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++
Java
PHP
Python

Java
PHP
Python

Java
Kotlin
Scala

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

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

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

in-memory journaling

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 rights for users, groups and roles

token access

Role-based access control

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

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Apache Software Foundation Announces Apache® Hive 4.0
30 April 2024, GlobeNewswire

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

What Is Apache Iceberg?
26 February 2024, IBM

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

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

Trinity College spinout TerminusDB secures €3.6m in investment
15 March 2021, The Irish Times

[MCR2030-CAMS-ARISE-UNDRR Webinar] Preventing cascading failures of critical assets: Using the Open-Source ...
12 April 2022, United Nations Office for Disaster Risk Reduction

Irish start-ups received €28m from Enterprise Ireland in 2021
7 April 2022, SiliconRepublic.com

Bus Terminus Update - April 26th
26 April 2021, Around DB and Life on Lantau

provided by Google News

Share this page