DBMS > Drizzle vs. Graphite vs. Newts vs. VoltDB

System Properties Comparison Drizzle vs. Graphite vs. Newts vs. VoltDB

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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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Time Series DBMS based on Cassandra

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

github.com/graphite-project/graphite-web

opennms.github.io/newts

www.voltdb.com

Technical documentation

graphite.readthedocs.io

github.com/OpenNMS/newts/wiki

docs.voltdb.com

Developer

Drizzle project, originally started by Brian Aker

Chris Davis

OpenNMS Group

VoltDB Inc.

Initial release

2008

2006

2014

2010

Current release

7.2.4, September 2012

11.3, April 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Python

Java

Java, C++

Server operating systems

FreeBSD
Linux
OS X

Linux
Unix

Linux
OS X
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

yes

with proprietary extensions

yes

only a subset of SQL 99

APIs and other access methods

JDBC

HTTP API
Sockets

HTTP REST
Java API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C++
Java
PHP

JavaScript (Node.js)
Python

Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

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1 April 2022, Datanami

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

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12 June 2023, InfoWorld

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31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

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28 January 2016, The New Stack

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