DBMS > DolphinDB vs. Firebase Realtime Database vs. Microsoft Azure Table Storage vs. ObjectBox vs. SQLite

System Properties Comparison DolphinDB vs. Firebase Realtime Database vs. Microsoft Azure Table Storage vs. ObjectBox vs. SQLite

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.

A Wide Column Store for rapid development using massive semi-structured datasets

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Document store

Wide column store

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

Time Series DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.dolphindb.com

firebase.google.com/products/realtime-database

azure.microsoft.com/en-us/services/storage/tables

github.com/objectbox
objectbox.io

www.sqlite.org

Technical documentation

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

firebase.google.com/docs/database

docs.objectbox.io

www.sqlite.org/docs.html

Developer

DolphinDB, Inc

Google

acquired by Google 2014

Microsoft

ObjectBox Limited

Dwayne Richard Hipp

Initial release

2018

2012

2017

2000

Current release

v2.00.4, January 2022

4.0 (May 2024)

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free community version available

commercial

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Public Domain

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 and C++

Server operating systems

Linux
Windows

hosted

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

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

RESTful HTTP API

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

Java
JavaScript
Objective-C

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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Data sync between devices allowing occasional connected databases to work completely offline

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Administrators, Users, Groups

yes, based on authentication and database rules

Access rights based on private key authentication or shared access signatures

yes

More information provided by the system vendor

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