DBMS > Amazon SimpleDB vs. GeoSpock vs. Lovefield vs. Machbase Neo vs. RDF4J

System Properties Comparison Amazon SimpleDB vs. GeoSpock vs. Lovefield vs. Machbase Neo vs. RDF4J

Editorial information provided by DB-Engines

Name

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

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Spatial and temporal data processing engine for extreme data scale

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Time Series DBMS

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

aws.amazon.com/simpledb

geospock.com

google.github.io/lovefield

machbase.com

rdf4j.org

Technical documentation

docs.aws.amazon.com/simpledb

github.com/google/lovefield/blob/master/docs/spec_index.md

machbase.com/dbms

rdf4j.org/documentation

Developer

Amazon

GeoSpock

Google

Machbase

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2007

2014

2013

2004

Current release

2.0, September 2019

2.1.12, February 2017

V8.0, August 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free test version available

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java, Javascript

JavaScript

Java

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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

yes

All columns are indexed automatically

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Automatic sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

using MemoryDB

yes

volatile and lookup table

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users can be defined per table

simple password-based access control

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

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