DBMS > Amazon Redshift vs. GeoSpock vs. ObjectBox

System Properties Comparison Amazon Redshift vs. GeoSpock vs. ObjectBox

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Spatial and temporal data processing engine for extreme data scale

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

Object oriented DBMS

Secondary database models

Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

aws.amazon.com/redshift

geospock.com

objectbox.io

Technical documentation

docs.aws.amazon.com/redshift

docs.objectbox.io

Developer

Amazon (based on PostgreSQL)

GeoSpock

ObjectBox Limited

Initial release

2012

2017

Current release

2.0, September 2019

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Javascript

C and C++

Server operating systems

hosted

Android
iOS
Linux
macOS
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

temporal, categorical

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI SQL for query only (using Presto)

APIs and other access methods

JDBC
ODBC

JDBC

Proprietary native API

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

online/offline synchronization between client and server

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

Access rights for users can be defined per table

yes

More information provided by the system vendor

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