DBMS > Graph Engine vs. Graphite vs. JaguarDB vs. RDF4J

System Properties Comparison Graph Engine vs. Graphite vs. JaguarDB vs. RDF4J

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Performant, highly scalable DBMS for AI and IoT applications

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

Primary database model

Graph DBMS
Key-value store

Time Series DBMS

Key-value store
Vector DBMS

RDF store

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

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

www.graphengine.io

github.com/graphite-project/graphite-web

www.jaguardb.com

rdf4j.org

Technical documentation

www.graphengine.io/docs/manual

graphite.readthedocs.io

www.jaguardb.com/support.html

rdf4j.org/documentation

Developer

Microsoft

Chris Davis

DataJaguar, Inc.

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

Initial release

2010

2006

2015

2004

Current release

3.3 July 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

GPL V3.0

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

.NET and C

Python

C++

the server part. Clients available in other languages

Java

Server operating systems

.NET

Linux
Unix

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

RESTful HTTP API

HTTP API
Sockets

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C#
C++
F#
Visual Basic

JavaScript (Node.js)
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

rights management via user accounts

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

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Trinity
30 October 2010, microsoft.com

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019
27 February 2019, Data Science Central

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

Collecting, storing, and analyzing your DevOps workloads with open-source Telegraf, Amazon Timestream, and Grafana
25 November 2020, AWS Blog

provided by Google News

Share this page