DBMS > Amazon DocumentDB vs. DataFS vs. GeoSpock vs. Hawkular Metrics

System Properties Comparison Amazon DocumentDB vs. DataFS vs. GeoSpock vs. Hawkular Metrics

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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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Spatial and temporal data processing engine for extreme data scale

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Secondary database models

Graph DBMS

Time Series DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Website

aws.amazon.com/documentdb

newdatabase.com

geospock.com

www.hawkular.org

Technical documentation

aws.amazon.com/documentdb/resources

dev.mobiland.com/Overview.xsp

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Mobiland AG

GeoSpock

Community supported by Red Hat

Initial release

2019

2018

2014

Current release

1.1.263, October 2022

2.0, September 2019

License

Commercial or Open Source

commercial

Open Source

Apache 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

Java, Javascript

Java

Server operating systems

hosted

Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

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

temporal, categorical

SQL

Support of SQL

ANSI SQL for query only (using Presto)

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

.NET Client API
Proprietary client DLL
WinRT client

JDBC

HTTP REST

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C#
C++
VB.Net

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

Triggers

no, except callback-events from server when changes happened

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

Automatic sharding

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

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.

User concepts

Access control

Access rights for users and roles

Windows-Profile

Access rights for users can be defined per table

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More resources

Recent citations in the news

A hybrid approach for homogeneous migration to an Amazon DocumentDB elastic cluster | Amazon Web Services
4 June 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

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20 May 2024, AWS Blog

Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services
8 March 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

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20 June 2019, AWS Blog

GeoSpock launches Spatial Big Data Platform 2.0
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