DBMS > Amazon Redshift vs. Apache IoTDB vs. GigaSpaces vs. SAP SQL Anywhere vs. Valentina Server

System Properties Comparison Amazon Redshift vs. Apache IoTDB vs. GigaSpaces vs. SAP SQL Anywhere vs. Valentina Server

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Object-relational database and reports server

Primary database model

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

aws.amazon.com/redshift

iotdb.apache.org

www.gigaspaces.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.valentina-db.net

Technical documentation

docs.aws.amazon.com/redshift

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

docs.gigaspaces.com/latest/landing.html

help.sap.com/docs/SAP_SQL_Anywhere

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Gigaspaces Technologies

SAP

formerly Sybase

Paradigma Software

Initial release

2012

2018

2000

1992

1999

Current release

1.1.0, April 2023

15.5, September 2020

17, July 2015

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial licenses available

commercial

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

Java, C++, .Net

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux
macOS
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

XML can be used for describing objects metadata

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

SQL-99 for query and DML statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
Native API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
HTTP API
JDBC
ODBC

ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

.Net
C++
Java
Python
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, in C/C++, Java, .Net or Perl

yes

Triggers

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

none

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

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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 capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Role-based access control

fine grained access rights according to SQL-standard

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