DBMS > Amazon Redshift vs. ObjectBox

System Properties Comparison Amazon Redshift vs. ObjectBox

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Our visitors often compare Amazon Redshift and ObjectBox with Firebase Realtime Database, DuckDB and MongoDB.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Primary database model

Relational DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Time Series DBMS

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

Score	14.52
Rank	#38	Overall
	#23	Relational DBMS

Score	1.07
Rank	#174	Overall
	#6	Object oriented DBMS
	#11	Vector DBMS

Website

aws.amazon.com/redshift

github.com/objectbox
objectbox.io

Technical documentation

docs.aws.amazon.com/redshift

docs.objectbox.io

Developer

Amazon (based on PostgreSQL)

ObjectBox Limited

Initial release

2012

2017

Current release

4.0 (May 2024)

License

Commercial or Open Source

commercial

Bindings are released under Apache 2.0

Apache License 2.0

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

C and C++

Server operating systems

hosted

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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

APIs and other access methods

JDBC
ODBC

Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Data sync between devices allowing occasional connected databases to work completely offline

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

More information provided by the system vendor

News

Why do we need Edge Computing for a sustainable future?
30 November 2024

IoT, Edge Computing, and Digitalization in Healthcare
22 November 2024

The Embedded Database for C++ and C
11 November 2024

The Critical Role of Databases for Edge AI
11 November 2024

Bi-directional Offline-First Data Sync with MongoDB and ObjectBox
21 October 2024

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