DBMS > Fujitsu Enterprise Postgres vs. IBM Db2 Event Store vs. Kingbase vs. LokiJS vs. Microsoft SQL Server

System Properties Comparison Fujitsu Enterprise Postgres vs. IBM Db2 Event Store vs. Kingbase vs. LokiJS vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Distributed Event Store optimized for Internet of Things use cases

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

In-memory JavaScript DBMS

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

www.postgresql.fastware.com

www.ibm.com/products/db2-event-store

www.kingbase.com.cn

github.com/techfort/LokiJS

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

Technical documentation

www.postgresql.fastware.com/product-manuals

www.ibm.com/docs/en/db2-event-store

techfort.github.io/LokiJS

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

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

IBM

BeiJing KINGBASE Information technologies inc.

Microsoft

Initial release

2017

1999

2014

1989

Current release

Fujitsu Enterprise Postgres 14, January 2022

2.0

V8.0, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C and Java

JavaScript

C++

Server operating systems

Linux
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

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

Linux
Windows

Data scheme

yes

schema-free

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

via views

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

Standard with numerous extensions

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

JavaScript API

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

Supported programming languages

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

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

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

JavaScript

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

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

View functions in JavaScript

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

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

none

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

Active-active shard replication

yes

none

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

fine grained access rights according to SQL-standard

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