DBMS > Kyligence Enterprise vs. OrigoDB vs. Prometheus vs. SAP HANA vs. Transbase

System Properties Comparison Kyligence Enterprise vs. OrigoDB vs. Prometheus vs. SAP HANA vs. Transbase

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, built on top of Apache Kylin

A fully ACID in-memory object graph database

Open-source Time Series DBMS and monitoring system

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

kyligence.io/kyligence-enterprise

origodb.com

prometheus.io

www.sap.com/products/hana.html

www.transaction.de/en/products/transbase.html

Technical documentation

origodb.com/docs

prometheus.io/docs

help.sap.com/hana

www.transaction.de/en/products/transbase/features.html

Developer

Kyligence, Inc.

Robert Friberg et al

SAP

Transaction Software GmbH

Initial release

2016

2009

under the name LiveDB

2015

2010

1987

Current release

2.0 SPS07 (April 4, 2023), April 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

Linux

Linux
Windows

Appliance or cloud-service

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

Numeric data only

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.

can be achieved using .NET

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
HTTP API
LINQ

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

by Federation

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

yes

fine grained access rights according to SQL-standard

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