DBMS > Apache Kylin vs. EJDB vs. ITTIA vs. Microsoft SQL Server vs. PostgreSQL

System Properties Comparison Apache Kylin vs. EJDB vs. ITTIA vs. Microsoft SQL Server vs. PostgreSQL

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Edge Time Series DBMS with Real-Time Stream Processing

Microsofts flagship relational DBMS

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

kylin.apache.org

github.com/Softmotions/ejdb

www.ittia.com

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

www.postgresql.org

Technical documentation

kylin.apache.org/docs

github.com/Softmotions/ejdb/blob/master/README.md

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

www.postgresql.org/docs

Developer

Apache Software Foundation, originally contributed from eBay Inc

Softmotions

ITTIA L.L.C.

Microsoft

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2015

2012

2007

1989

1989: Postgres, 1996: PostgreSQL

Current release

3.1.0, July 2020

8.7

SQL Server 2022, November 2022

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2

commercial

restricted free version is available

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++

Server operating systems

Linux

server-less

Linux
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

in-process shared library

JDBC
ODBC
RESTful HTTP API
WebSocket

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

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

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C++
JavaScript (Node.js)
Python

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

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

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes, multi-version concurrency control (MVCC)

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

Database file passwords

fine grained access rights according to SQL-standard

More information provided by the system vendor

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