DBMS > Bangdb vs. HugeGraph vs. JaguarDB vs. SWC-DB vs. Valentina Server

System Properties Comparison Bangdb vs. HugeGraph vs. JaguarDB vs. SWC-DB vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

A fast-speed and highly-scalable Graph DBMS

Performant, highly scalable DBMS for AI and IoT applications

A high performance, scalable Wide Column DBMS

Object-relational database and reports server

Primary database model

Document store
Graph DBMS
Time Series DBMS

Graph DBMS

Key-value store
Vector DBMS

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

bangdb.com

github.com/hugegraph
hugegraph.apache.org

www.jaguardb.com

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

www.valentina-db.net

Technical documentation

docs.bangdb.com

hugegraph.apache.org/docs

www.jaguardb.com/support.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Sachin Sinha, BangDB

Baidu

DataJaguar, Inc.

Alex Kashirin

Paradigma Software

Initial release

2012

2018

2015

2020

1999

Current release

BangDB 2.0, October 2021

0.9

3.3 July 2023

0.5, April 2021

5.7.5

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2.0

Open Source

GPL V3.0

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

Linux
macOS
Unix

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL like support with command line tool

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

Proprietary protocol
Thrift

ODBC

Supported programming languages

C
C#
C++
Java
Python

Groovy
Java
Python

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

C++

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

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

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

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

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Users, roles and permissions

rights management via user accounts

fine grained access rights according to SQL-standard

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