DBMS > Amazon Redshift vs. Apache IoTDB vs. BigObject vs. Greenplum vs. SAP Advantage Database Server

System Properties Comparison Amazon Redshift vs. Apache IoTDB vs. BigObject vs. Greenplum vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

Analytic DBMS for real-time computations and queries

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Website

aws.amazon.com/redshift

iotdb.apache.org

bigobject.io

greenplum.org

www.sap.com/products/advantage-database-server.html

Technical documentation

docs.aws.amazon.com/redshift

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

docs.bigobject.io

docs.greenplum.org

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

BigObject, Inc.

Pivotal Software Inc.

Sybase, SAP

Initial release

2012

2018

2015

2005

1993

Current release

1.1.0, April 2023

7.0.0, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

Apache 2.0

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

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Linux
Windows

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.

yes

since Version 4.2

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
Native API

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

C
Java
Perl
Python
R

Delphi
Perl
PHP

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

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

none

Source-replica replication

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

caching of (temporary) tables can be configured

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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