DBMS > HugeGraph vs. Machbase Neo vs. Oracle Rdb vs. TimesTen

System Properties Comparison HugeGraph vs. Machbase Neo vs. Oracle Rdb vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

TimeSeries DBMS for AIoT and BigData

In-Memory RDBMS compatible to Oracle

Primary database model

Graph DBMS

Time Series DBMS

Relational DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

machbase.com

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

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

Technical documentation

hugegraph.apache.org/docs

machbase.com/dbms

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

docs.oracle.com/database/timesten-18.1

Developer

Baidu

Machbase

Oracle, originally developed by Digital Equipment Corporation (DEC)

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2013

1984

1998

Current release

0.9

V8.0, August 2023

7.4.1.1, 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

commercial

Cloud-based only

Only available as a cloud 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

Linux
macOS
Unix

Linux
macOS
Windows

HP Open VMS

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

Java API
RESTful HTTP API
TinkerPop Gremlin

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Groovy
Java
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Users, roles and permissions

simple password-based access control

fine grained access rights according to SQL-standard

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