DBMS > Apache IoTDB vs. Newts vs. NSDb vs. SAP Adaptive Server vs. Transbase

System Properties Comparison Apache IoTDB vs. Newts vs. NSDb vs. SAP Adaptive Server vs. Transbase

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Time Series DBMS based on Cassandra

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

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

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

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

iotdb.apache.org

opennms.github.io/newts

nsdb.io

www.sap.com/products/technology-platform/sybase-ase.html

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

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

github.com/OpenNMS/newts/wiki

nsdb.io/Architecture

help.sap.com/docs/SAP_ASE

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

Developer

Apache Software Foundation

OpenNMS Group

SAP, Sybase

Transaction Software GmbH

Initial release

2018

2014

2017

1987

Current release

1.1.0, April 2023

16.0

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

free development license

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

Java, Scala

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Linux
macOS

AIX
HP-UX
Linux
Solaris
Unix
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

HTTP REST
Java API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

Java
Scala

C
C++
Cobol
Java
Java
Perl
PHP
Python

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

Server-side scripts

Stored procedures

yes

Java and Transact-SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

based on Cassandra

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Using Apache Lucene

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

yes

fine grained access rights according to SQL-standard

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