DBMS > HarperDB vs. Prometheus vs. RDF4J

System Properties Comparison HarperDB vs. Prometheus vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Open-source Time Series DBMS and monitoring system

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

Primary database model

Document store

Time Series DBMS

RDF store

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

Score	0.55
Rank	#252	Overall
	#38	Document stores

Score	7.92
Rank	#51	Overall
	#2	Time Series DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

www.harperdb.io

prometheus.io

rdf4j.org

Technical documentation

docs.harperdb.io/docs

prometheus.io/docs

rdf4j.org/documentation

Developer

HarperDB

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

Initial release

2017

2015

2004

Current release

3.1, August 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 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

Node.js

Java

Server operating systems

Linux
OS X

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

dynamic schema

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

JSON data types

Numeric data only

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 of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

A table resides as a whole on one (or more) nodes in a cluster

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using LMDB

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

Access rights for users and roles

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More resources

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