DBMS > Amazon SimpleDB vs. GeoMesa vs. JanusGraph vs. Microsoft Azure Table Storage vs. ObjectBox

System Properties Comparison Amazon SimpleDB vs. GeoMesa vs. JanusGraph vs. Microsoft Azure Table Storage vs. ObjectBox

Editorial information provided by DB-Engines

Name

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A Wide Column Store for rapid development using massive semi-structured datasets

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Secondary database models

Time Series DBMS

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

aws.amazon.com/simpledb

www.geomesa.org

janusgraph.org

azure.microsoft.com/en-us/services/storage/tables

objectbox.io

Technical documentation

docs.aws.amazon.com/simpledb

www.geomesa.org/documentation/stable/user/index.html

docs.janusgraph.org

docs.objectbox.io

Developer

Amazon

CCRi and others

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

ObjectBox Limited

Initial release

2007

2014

2017

2012

2017

Current release

5.0.0, May 2024

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

Java

C and C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

hosted

Android
iOS
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

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

yes

All columns are indexed automatically

yes

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

Proprietary native API

Supported programming languages

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

Clojure
Java
Python

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

depending on storage layer

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

depending on storage layer

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

depending on storage layer

User concepts

Access control

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

yes

depending on the DBMS used for storage

User authentification and security via Rexster Graph Server

Access rights based on private key authentication or shared access signatures

yes

More information provided by the system vendor

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More resources

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Recent citations in the news

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