DBMS > AntDB vs. Firebase Realtime Database vs. MarkLogic vs. Splice Machine

System Properties Comparison AntDB vs. Firebase Realtime Database vs. MarkLogic vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

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

Operational and transactional Enterprise NoSQL database

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

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

Score	0.25
Rank	#303	Overall
	#137	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

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

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

firebase.google.com/products/realtime-database

www.marklogic.com

splicemachine.com

Technical documentation

firebase.google.com/docs/database

docs.marklogic.com

splicemachine.com/how-it-works

Social network pages

Developer

AsiaInfo Technologies Limited

Google

acquired by Google 2014

MarkLogic Corp.

Splice Machine

Initial release

2012

2001

2014

Current release

11.0, December 2022

3.1, March 2021

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

AGPL 3.0, 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++

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

Schema can be enforced

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL2016 compliant

yes

SQL92

yes

APIs and other access methods

JDBC
MySQL protocol compliant
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java
JavaScript
Objective-C

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

via XQuery or JavaScript

yes

Java

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Yes, via Full Spark Integration

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

ACID

yes

ACID

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes, with Range Indexes

yes

User concepts

Access control

yes, based on authentication and database rules

Role-based access control at the document and subdocument levels

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

AntDB was initiated in 2008. On the core system of operators, AntDB provides online...
» more

Competitive advantages

HTAP mixed load: AntDB is a universal, enterprise-level distributed relational database,...
» more

Typical application scenarios

As the core software of large enterprise, AntDB supports multi-scenario deployment....
» more

Key customers

China Mobile, China Telecom, China Unicom, Aeon Life, China Mobile Tietong, CITIC...
» more

Market metrics

More than 1 billion subscribers in 24 provinces across China are served by AntDB...
» more

Licensing and pricing models

Certificates and licenses CMMI5 Certificate licensed by CMMI Institute IT Product...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

AntDB: Answer to Database Evolution - Hyperconverged All-in-One Streaming Engine
22 June 2023, Bei Mo, AntDB (sponsor)

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Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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