DBMS > Amazon DocumentDB vs. Graph Engine vs. OushuDB vs. Warp 10

System Properties Comparison Amazon DocumentDB vs. Graph Engine vs. OushuDB vs. Warp 10

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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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store

Graph DBMS
Key-value store

Relational DBMS

Time Series 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	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

aws.amazon.com/documentdb

www.graphengine.io

www.oushu.com/product/oushuDB

www.warp10.io

Technical documentation

aws.amazon.com/documentdb/resources

www.graphengine.io/docs/manual

www.oushu.com/documentation

www.warp10.io/content/02_Getting_started

Developer

Microsoft

Oushu

SenX

Initial release

2019

2010

2015

Current release

4.0.1, August 2020

License

Commercial or Open Source

commercial

Open Source

MIT License

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

.NET and C

Java

Server operating systems

hosted

.NET

Linux

Linux
OS X
Windows

Data scheme

schema-free

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

SQL

Support of SQL

Full-featured ANSI SQL support

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
F#
Visual Basic

C
C++

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes

Sharding

based on HBase

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 HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

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

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

Kerberos, SSL and role based access

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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