DBMS > Amazon Redshift vs. ObjectBox vs. Yaacomo

System Properties Comparison Amazon Redshift vs. ObjectBox vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Large scale data warehouse service for use with business intelligence tools

Extremely fast embedded database for small devices, IoT and Mobile

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	1.22
Rank	#172	Overall
	#5	Object oriented DBMS

Website

aws.amazon.com/redshift

objectbox.io

yaacomo.com

Technical documentation

docs.aws.amazon.com/redshift

docs.objectbox.io

Developer

Amazon (based on PostgreSQL)

ObjectBox Limited

Q2WEB GmbH

Initial release

2012

2017

2009

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Server operating systems

hosted

Android
iOS
Linux
macOS
Windows

Android
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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

Proprietary native API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

online/offline synchronization between client and server

Source-replica replication

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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