DBMS > Amazon DocumentDB vs. HugeGraph vs. Machbase Neo vs. SAP HANA

System Properties Comparison Amazon DocumentDB vs. HugeGraph vs. Machbase Neo vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

TimeSeries DBMS for AIoT and BigData

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

aws.amazon.com/documentdb

github.com/hugegraph
hugegraph.apache.org

machbase.com

www.sap.com/products/hana.html

Technical documentation

aws.amazon.com/documentdb/resources

hugegraph.apache.org/docs

machbase.com/dbms

help.sap.com/hana

Developer

Baidu

Machbase

SAP

Initial release

2019

2018

2013

2010

Current release

0.9

V8.0, August 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free test version available

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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

Linux
macOS
Unix

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java API
RESTful HTTP API
TinkerPop Gremlin

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

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Groovy
Java
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

yes

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

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

edges in graph

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.

yes

volatile and lookup table

yes

User concepts

Access control

Access rights for users and roles

Users, roles and permissions

simple password-based access control

yes

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