DBMS > HBase vs. Newts vs. Quasardb vs. Stardog

System Properties Comparison HBase vs. Newts vs. Quasardb vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Wide column store

Time Series DBMS

Graph DBMS
RDF store

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

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

hbase.apache.org

opennms.github.io/newts

quasar.ai

www.stardog.com

Technical documentation

hbase.apache.org/book.html

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

docs.stardog.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

OpenNMS Group

quasardb

Stardog-Union

Initial release

2008

2014

2009

2010

Current release

2.3.4, January 2021

3.14.1, January 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

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

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

schema-free, schema definition possible

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

integer and binary

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.

Import/export of XML data possible

Secondary indexes

yes

with tags

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Java API
RESTful HTTP API
Thrift

HTTP REST
Java API

HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Single row ACID (across millions of columns)

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 Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Cryptographically strong user authentication and audit trail

Access rights for users and roles

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More resources

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