DBMS > Amazon Redshift vs. Apache IoTDB vs. Sadas Engine vs. TerminusDB

System Properties Comparison Amazon Redshift vs. Apache IoTDB vs. Sadas Engine vs. TerminusDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

Primary database model

Secondary database models

Document store
RDF store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

aws.amazon.com/redshift

iotdb.apache.org

www.sadasengine.com

terminusdb.com

Technical documentation

docs.aws.amazon.com/redshift

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

terminusdb.github.io/terminusdb/#

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

SADAS s.r.l.

DataChemist Ltd.

Initial release

2012

2018

2006

2018

Current release

1.1.0, April 2023

8.0

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free trial version available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Prolog, Rust

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

AIX
Linux
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

JDBC
Native API

JDBC
ODBC
Proprietary protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

Journaling Streams

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

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

in-memory journaling

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users, groups and roles according to SQL-standard

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.