DBMS > Amazon DocumentDB vs. Ehcache vs. Machbase Neo vs. Oracle Rdb

System Properties Comparison Amazon DocumentDB vs. Ehcache vs. Machbase Neo 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 widely adopted Java cache with tiered storage options

TimeSeries DBMS for AIoT and BigData

Primary database model

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

aws.amazon.com/documentdb

www.ehcache.org

machbase.com

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

Technical documentation

aws.amazon.com/documentdb/resources

www.ehcache.org/documentation

machbase.com/dbms

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

Developer

Terracotta Inc, owned by Software AG

Machbase

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2019

2009

2013

1984

Current release

3.10.0, March 2022

V8.0, August 2023

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

free test version available

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

Java

Server operating systems

hosted

All OS with a Java VM

Linux
macOS
Windows

HP Open VMS

Data scheme

schema-free

yes

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

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JCache

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

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

by using Terracotta Server

selectable replication factor

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

Tunable Consistency (Strong, Eventual, Weak)

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

supports JTA and can work as an XA resource

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

Access rights for users and roles

simple password-based access control

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