DBMS > Newts vs. OrigoDB vs. SAP HANA

System Properties Comparison Newts vs. OrigoDB vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS based on Cassandra

A fully ACID in-memory object graph database

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

Primary database model

Time Series DBMS

Document store
Object oriented 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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

opennms.github.io/newts

origodb.com

www.sap.com/products/hana.html

Technical documentation

github.com/OpenNMS/newts/wiki

origodb.com/docs

help.sap.com/hana

Developer

OpenNMS Group

Robert Friberg et al

SAP

Initial release

2014

2009

under the name LiveDB

2010

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

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

Server operating systems

Linux
OS X
Windows

Linux
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST
Java API

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Supported programming languages

Java

.Net

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

depending on model

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

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

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