DBMS > NSDb vs. OrigoDB vs. SAP IQ vs. TerminusDB

System Properties Comparison NSDb vs. OrigoDB vs. SAP IQ vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

Columnar RDBMS optimized for Big Data analytics

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

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

column-oriented

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	2.56
Rank	#106	Overall
	#52	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

nsdb.io

origodb.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

terminusdb.com

Technical documentation

nsdb.io/Architecture

origodb.com/docs

help.sap.com/docs/SAP_IQ

terminusdb.github.io/terminusdb/#

Developer

Robert Friberg et al

SAP, formerly Sybase

DataChemist Ltd.

Initial release

2017

2009

under the name LiveDB

1994

2018

Current release

16.1 SPS04, April 2019

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Scala

Prolog, Rust

Server operating systems

Linux
macOS

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
ODBC
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Java
Scala

.Net

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

shared disk or shared nothing architectures with SAP IQ Multiplexer

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

SAP/Sybase Replication Server

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Using Apache Lucene

yes

Write ahead log

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

Role based authorization

fine grained access rights according to SQL-standard

Role-based access control

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