DBMS > Amazon DocumentDB vs. Graph Engine vs. Hawkular Metrics vs. Oracle Rdb

System Properties Comparison Amazon DocumentDB vs. Graph Engine vs. Hawkular Metrics vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Primary database model

Document store

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Website

aws.amazon.com/documentdb

www.graphengine.io

www.hawkular.org

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

aws.amazon.com/documentdb/resources

www.graphengine.io/docs/manual

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

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Microsoft

Community supported by Red Hat

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2019

2010

2014

1984

Current release

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

commercial

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

.NET and C

Java

Server operating systems

hosted

.NET

Linux
OS X
Windows

HP Open VMS

Data scheme

schema-free

yes

schema-free

Flexible Schema (defined schema, partial schema, 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

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

HTTP REST

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
F#
Visual Basic

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

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

Immediate Consistency

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

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Access rights for users and roles

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More resources

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