DBMS > Dragonfly vs. HBase vs. NSDb vs. RDF4J

System Properties Comparison Dragonfly vs. HBase vs. NSDb vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Primary database model

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

hbase.apache.org

nsdb.io

rdf4j.org

Technical documentation

www.dragonflydb.io/docs

hbase.apache.org/book.html

nsdb.io/Architecture

rdf4j.org/documentation

Developer

DragonflyDB team and community contributors

Apache Software Foundation

Apache top-level project, originally developed by Powerset

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

Initial release

2023

2008

2017

2004

Current release

1.0, March 2023

2.3.4, January 2021

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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++

Java

Java, Scala

Java

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Linux
macOS

Linux
OS X
Unix
Windows

Data scheme

scheme-free

schema-free, schema definition possible

yes

RDF Schemas

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

options to bring your own types, AVRO

yes: int, bigint, decimal, 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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

Java API
RESTful HTTP API
Thrift

gRPC
HTTP REST
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Coprocessors in Java

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

Single row ACID (across millions of columns)

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

Password-based authentication

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

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More resources

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13 May 2013, Paul Andlinger

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