DBMS > Apache Kylin vs. MonetDB vs. SAP HANA vs. TerminusDB

System Properties Comparison Apache Kylin vs. MonetDB vs. SAP HANA vs. TerminusDB

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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

A relational database management system that stores data in columns

In-memory, column based data store. Available as appliance or cloud service

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
RDF store

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

Score	1.14
Rank	#171	Overall
	#77	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

kylin.apache.org

www.monetdb.org

www.sap.com/products/hana.html

terminusdb.com

Technical documentation

kylin.apache.org/docs

www.monetdb.org/Documentation

help.sap.com/hana

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation, originally contributed from eBay Inc

MonetDB BV

SAP

DataChemist Ltd.

Initial release

2015

2004

2010

2018

Current release

3.1.0, July 2020

Dec2023 (11.49), December 2023

2.0 SPS07 (April 4, 2023), April 2023

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Prolog, Rust

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL 2003 with some extensions

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

yes, in SQL, C, R

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

yes

Journaling Streams

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

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Role-based access control

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