DBMS > Drizzle vs. Graph Engine vs. Quasardb vs. SiteWhere

System Properties Comparison Drizzle vs. Graph Engine vs. Quasardb vs. SiteWhere

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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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Distributed, high-performance timeseries database

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

www.graphengine.io

quasar.ai

github.com/sitewhere/sitewhere

Technical documentation

www.graphengine.io/docs/manual

doc.quasar.ai/master

sitewhere1.sitewhere.io/index.html

Developer

Drizzle project, originally started by Brian Aker

Microsoft

quasardb

SiteWhere

Initial release

2008

2010

2009

2010

Current release

7.2.4, September 2012

3.14.1, January 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

MIT License

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Common Public Attribution License Version 1.0

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++

.NET and C

C++

Java

Server operating systems

FreeBSD
Linux
OS X

.NET

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC

RESTful HTTP API

HTTP API

HTTP REST

Supported programming languages

C
C++
Java
PHP

C#
C++
F#
Visual Basic

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

consistent hashing

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept

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More resources

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