DBMS > Drizzle vs. HugeGraph vs. Netezza vs. ObjectBox

System Properties Comparison Drizzle vs. HugeGraph vs. Netezza vs. ObjectBox

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A fast-speed and highly-scalable Graph DBMS

Data warehouse and analytics appliance part of IBM PureSystems

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.ibm.com/products/netezza

objectbox.io

Technical documentation

hugegraph.apache.org/docs

docs.objectbox.io

Developer

Drizzle project, originally started by Brian Aker

Baidu

IBM

ObjectBox Limited

Initial release

2008

2018

2000

2017

Current release

7.2.4, September 2012

0.9

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2.0

commercial

Open Source

Apache License 2.0

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

C++

Java

C and C++

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS
Unix

Linux

included in appliance

Android
iOS
Linux
macOS
Windows

Data scheme

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

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
OLE DB

Proprietary native API

Supported programming languages

C
C++
Java
PHP

Groovy
Java
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

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

Source-replica replication

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users, roles and permissions

Users with fine-grained authorization concept

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

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