DBMS > AntDB vs. Firebase Realtime Database vs. LeanXcale vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB

System Properties Comparison AntDB vs. Firebase Realtime Database vs. LeanXcale vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB

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.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Widely used in-process key-value store

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	0.23
Rank	#317	Overall
	#141	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

firebase.google.com/products/realtime-database

www.leanxcale.com

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

firebase.google.com/docs/database

docs.microsoft.com/azure/synapse-analytics

docs.oracle.com/cd/E17076_05/html/index.html

Developer

AsiaInfo Technologies Limited

Google

acquired by Google 2014

LeanXcale

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2012

2015

2016

1994

Current release

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

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++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL2016 compliant

yes

through Apache Derby

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
MySQL protocol compliant
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

C
Java
Scala

C#
Java
PHP

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Transact SQL

Triggers

yes

Callbacks are triggered when data changes

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

yes

ACID

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

yes, based on authentication and database rules

yes

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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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