DBMS > Firebase Realtime Database vs. Lovefield vs. Machbase Neo vs. MarkLogic vs. Microsoft Azure Cosmos DB

System Properties Comparison Firebase Realtime Database vs. Lovefield vs. Machbase Neo vs. MarkLogic vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

Operational and transactional Enterprise NoSQL database

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store

Relational DBMS

Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

firebase.google.com/products/realtime-database

google.github.io/lovefield

machbase.com

www.marklogic.com

azure.microsoft.com/services/cosmos-db

Technical documentation

firebase.google.com/docs/database

github.com/google/lovefield/blob/master/docs/spec_index.md

machbase.com/dbms

docs.marklogic.com

learn.microsoft.com/azure/cosmos-db

Developer

Google

acquired by Google 2014

Google

Machbase

MarkLogic Corp.

Microsoft

Initial release

2012

2014

2013

2001

2014

Current release

2.1.12, February 2017

V8.0, August 2023

11.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free test version available

commercial

restricted free version is available

commercial

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

JavaScript

C++

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

schema-free

Schema can be enforced

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

SQL92

SQL-like query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Java
JavaScript
Objective-C

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

via XQuery or JavaScript

JavaScript

Triggers

Callbacks are triggered when data changes

Using read-only observers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

can act as a resource manager in an XA/JTA transaction

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

volatile and lookup table

yes, with Range Indexes

User concepts

Access control

yes, based on authentication and database rules

simple password-based access control

Role-based access control at the document and subdocument levels

Access rights can be defined down to the item level

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