DBMS > BaseX vs. DolphinDB vs. Firebase Realtime Database vs. Hawkular Metrics vs. SiteWhere

System Properties Comparison BaseX vs. DolphinDB vs. Firebase Realtime Database vs. Hawkular Metrics vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

Relational DBMS

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

basex.org

www.dolphindb.com

firebase.google.com/products/realtime-database

www.hawkular.org

github.com/sitewhere/sitewhere

Technical documentation

docs.basex.org

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

firebase.google.com/docs/database

www.hawkular.org/hawkular-metrics/docs/user-guide

sitewhere1.sitewhere.io/index.html

Developer

BaseX GmbH

DolphinDB, Inc

Google

acquired by Google 2014

Community supported by Red Hat

SiteWhere

Initial release

2007

2018

2012

2014

2010

Current release

10.7, August 2023

v2.00.4, January 2022

License

Commercial or Open Source

Open Source

BSD license

commercial

free community version available

commercial

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

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

Java

C++

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

XQuery supports types

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

Java
JavaScript
Objective-C

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

Triggers

yes

via events

Callbacks are triggered when data changes

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

based on Cassandra

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

based on Cassandra

selectable replication factor

based on HBase

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

yes

Concurrency

Support for concurrent manipulation of data

yes

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

Users with fine-grained authorization concept on 4 levels

Administrators, Users, Groups

yes, based on authentication and database rules

Users with fine-grained authorization concept

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Related products and services

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More resources

DB-Engines blog posts

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