DBMS > HugeGraph vs. MaxDB vs. RavenDB vs. SiteWhere

System Properties Comparison HugeGraph vs. MaxDB vs. RavenDB vs. SiteWhere

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

A robust and reliable RDBMS optimized to run all major SAP solutions

Open Source Operational and Transactional Enterprise NoSQL Document Database

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

github.com/hugegraph
hugegraph.apache.org

maxdb.sap.com

ravendb.net

github.com/sitewhere/sitewhere

Technical documentation

hugegraph.apache.org/docs

maxdb.sap.com/documentation

ravendb.net/docs

sitewhere1.sitewhere.io/index.html

Developer

Baidu

SAP, acquired from Software AG (Adabas-D) in 1997

Hibernating Rhinos

SiteWhere

Initial release

2018

1984

2010

Current release

0.9

7.9.10.12, February 2024

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Limited community edition free

Open Source

AGPL version 3, commercial license available

Open Source

Common Public Attribution License Version 1.0

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

Java

C++

Java

Server operating systems

Linux
macOS
Unix

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like query language (RQL)

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
WebDAV

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP REST

Supported programming languages

Groovy
Java
Python

.Net
C#
Java
Perl
PHP
Python

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

Multi-source replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

Users with fine-grained authorization concept

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

Recent citations in the news

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

SAP Content Server High Availability using Amazon EFS and SUSE | Amazon Web Services
30 December 2020, AWS Blog

SAP Aligns Mainstream Maintenance Commitments Across Its Enterprise Solutions
11 August 2020, SAP News

SIOS looks to boost SAP HANA automated replication
29 March 2023, TechTarget

Remotely Exploitable Vulnerabilities in SAP Compression Algorithms
13 May 2015, Threatpost

Your SAP HANA Cheat Sheet: Milestones, Terms and More
14 May 2012, SiliconANGLE News

provided by Google News

RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
3 October 2023, PR Newswire

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

RavenDB Adds Graph Queries
15 May 2019, Datanami

provided by Google News

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

Share this page