DBMS > Axibase vs. Firebase Realtime Database vs. InterSystems Caché vs. Kingbase vs. Microsoft SQL Server

System Properties Comparison Axibase vs. Firebase Realtime Database vs. InterSystems Caché vs. Kingbase vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

A multi-model DBMS and application server

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Microsofts flagship relational DBMS

Primary database model

Time Series DBMS

Document store

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

axibase.com/docs/atsd/finance

firebase.google.com/products/realtime-database

www.intersystems.com/products/cache

www.kingbase.com.cn

www.microsoft.com/en-us/sql-server

Technical documentation

firebase.google.com/docs/database

docs.intersystems.com

learn.microsoft.com/en-US/sql/sql-server

Developer

Axibase Corporation

Google

acquired by Google 2014

InterSystems

BeiJing KINGBASE Information technologies inc.

Microsoft

Initial release

2013

2012

1997

1999

1989

Current release

15585

2018.1.4, May 2020

V8.0, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and Java

C++

Server operating systems

Linux

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

schema-free

depending on used data model

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL-like query language

yes

Standard with numerous extensions

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Java
JavaScript
Objective-C

C#
C++
Java

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

yes

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by range, list and hash) and vertical partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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