DBMS > HugeGraph vs. RavenDB vs. SAP HANA vs. SWC-DB vs. Transbase

System Properties Comparison HugeGraph vs. RavenDB vs. SAP HANA vs. SWC-DB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

In-memory, column based data store. Available as appliance or cloud service

A high performance, scalable Wide Column DBMS

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	2.92
Rank	#101	Overall
	#18	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

ravendb.net

www.sap.com/products/hana.html

github.com/kashirin-alex/swc-db
www.swcdb.org

www.transaction.de/en/products/transbase.html

Technical documentation

hugegraph.apache.org/docs

ravendb.net/docs

help.sap.com/hana

www.transaction.de/en/products/transbase/features.html

Developer

Baidu

Hibernating Rhinos

SAP

Alex Kashirin

Transaction Software GmbH

Initial release

2018

2010

2020

1987

Current release

0.9

5.4, July 2022

2.0 SPS07 (April 4, 2023), April 2023

0.5, April 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL version 3, commercial license available

commercial

Open Source

GPL V3

commercial

free development license

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

C and C++

Server operating systems

Linux
macOS
Unix

Linux
macOS
Raspberry Pi
Windows

Appliance or cloud-service

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

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

SQL-like query language (RQL)

yes

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

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

JDBC
ODBC

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Groovy
Java
Python

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

C++

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication

yes

Source-replica replication

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

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

ACID

yes

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

Authorization levels configured per client per database

yes

fine grained access rights according to SQL-standard

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