DBMS > NSDb vs. SAP IQ

System Properties Comparison NSDb vs. SAP IQ

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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

Columnar RDBMS optimized for Big Data analytics

Primary database model

Time Series DBMS

Relational DBMS

column-oriented

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

Score	0.00
Rank	#379	Overall
	#41	Time Series DBMS

Score	2.42
Rank	#105	Overall
	#52	Relational DBMS

Website

nsdb.io

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

Technical documentation

nsdb.io/Architecture

help.sap.com/docs/SAP_IQ

Developer

SAP, formerly Sybase

Initial release

2017

1994

Current release

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Scala

Server operating systems

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

SAP/Sybase Replication Server

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

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

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