DBMS > DolphinDB vs. Firebase Realtime Database vs. Interbase vs. JanusGraph

System Properties Comparison DolphinDB vs. Firebase Realtime Database vs. Interbase vs. JanusGraph

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Editorial information provided by DB-Engines

Name

Description

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.

Light-weight proven RDBMS

originally from Borland

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Primary database model

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Website

www.dolphindb.com

firebase.google.com/products/realtime-database

www.embarcadero.com/products/interbase

janusgraph.org

Technical documentation

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

firebase.google.com/docs/database

docs.embarcadero.com/products/interbase

docs.janusgraph.org

Developer

DolphinDB, Inc

Google

acquired by Google 2014

Embarcadero

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2018

2012

1984

2017

Current release

v2.00.4, January 2022

InterBase 2020, December 2019

0.6.3, February 2023

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

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++

Java

Server operating systems

Linux
Windows

hosted

Android
iOS
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

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

Java
JavaScript
Objective-C

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

yes

Interbase procedure and trigger language

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Interbase Change Views

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

yes

User concepts

Access control

Administrators, Users, Groups

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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