DBMS > Bangdb vs. HugeGraph vs. IBM Db2 warehouse vs. Percona Server for MongoDB vs. RRDtool

System Properties Comparison Bangdb vs. HugeGraph vs. IBM Db2 warehouse vs. Percona Server for MongoDB vs. RRDtool

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

Cloud-based data warehousing service

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial 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	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

bangdb.com

github.com/hugegraph
hugegraph.apache.org

www.ibm.com/products/db2/warehouse

www.percona.com/mongodb/software/percona-server-for-mongodb

oss.oetiker.ch/rrdtool

Technical documentation

docs.bangdb.com

hugegraph.apache.org/docs

docs.percona.com/percona-distribution-for-mongodb

oss.oetiker.ch/rrdtool/doc

Developer

Sachin Sinha, BangDB

Baidu

IBM

Percona

Tobias Oetiker

Initial release

2012

2018

2014

2015

1999

Current release

BangDB 2.0, October 2021

0.9

3.4.10-2.10, November 2017

1.8.0, 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2.0

commercial

Open Source

GPL Version 2

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++

Java

C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux

Linux
macOS
Unix

hosted

Linux

HP-UX
Linux

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

Numeric data only

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/export of XML data possible

Exporting into and restoring from XML files possible

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

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
JDBC
ODBC
OLE DB

proprietary protocol using JSON

in-process shared library
Pipes

Supported programming languages

C
C#
C++
Java
Python

Groovy
Java
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

PL/SQL, SQL PL

JavaScript

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

none

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

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

none

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

by using the rrdcached daemon

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

via In-Memory Engine

yes

User concepts

Access control

yes (enterprise version only)

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights for users and roles

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