DBMS > Bangdb vs. DolphinDB vs. Firebase Realtime Database vs. H2 vs. OpenQM

System Properties Comparison Bangdb vs. DolphinDB vs. Firebase Realtime Database vs. H2 vs. OpenQM

Editorial information provided by DB-Engines

Name

Description

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

bangdb.com

www.dolphindb.com

firebase.google.com/products/realtime-database

www.h2database.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

docs.bangdb.com

docs.dolphindb.cn/en/help200/index.html

firebase.google.com/docs/database

www.h2database.com/html/main.html

Developer

Sachin Sinha, BangDB

DolphinDB, Inc

Google

acquired by Google 2014

Thomas Mueller

Rocket Software, originally Martin Phillips

Initial release

2012

2018

2012

2005

1993

Current release

BangDB 2.0, October 2021

v2.00.4, January 2022

2.2.220, July 2023

3.4-12

License

Commercial or Open Source

Open Source

BSD 3

commercial

free community version available

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPLv2, extended commercial license available

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++

C++

Java

Server operating systems

Linux

Linux
Windows

hosted

All OS with a Java VM

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Java
JavaScript
Objective-C

Java

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes, Notifications (with Streaming only)

Callbacks are triggered when data changes

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

horizontal partitioning

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

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)

Administrators, Users, Groups

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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