DBMS > Apache Kylin vs. IBM Db2 Event Store vs. PostGIS vs. SWC-DB

System Properties Comparison Apache Kylin vs. IBM Db2 Event Store vs. PostGIS vs. SWC-DB

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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

Distributed Event Store optimized for Internet of Things use cases

Spatial extension of PostgreSQL

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Spatial DBMS

Wide column store

Secondary database models

Relational DBMS

Time Series DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

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

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

kylin.apache.org

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

postgis.net

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

kylin.apache.org/docs

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

postgis.net/documentation

Developer

Apache Software Foundation, originally contributed from eBay Inc

IBM

Alex Kashirin

Initial release

2015

2017

2005

2020

Current release

3.1.0, July 2020

2.0

3.4.2, February 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

GPL v2.0

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

through the embedded Spark runtime

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

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

C++

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

based on PostgreSQL

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

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

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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