DBMS > DataFS vs. Drizzle vs. Graphite vs. Rockset

System Properties Comparison DataFS vs. Drizzle vs. Graphite vs. Rockset

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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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Secondary database models

Graph DBMS

Relational DBMS
Search engine

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

newdatabase.com

github.com/graphite-project/graphite-web

rockset.com

Technical documentation

dev.mobiland.com/Overview.xsp

graphite.readthedocs.io

docs.rockset.com

Developer

Mobiland AG

Drizzle project, originally started by Brian Aker

Chris Davis

Rockset

Initial release

2018

2008

2006

2019

Current release

1.1.263, October 2022

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Python

C++

Server operating systems

Windows

FreeBSD
Linux
OS X

Linux
Unix

hosted

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

Read-only SQL queries, including JOINs

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

JDBC

HTTP API
Sockets

HTTP REST

Supported programming languages

.Net
C
C#
C++
VB.Net

C
C++
Java
PHP

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

no, except callback-events from server when changes happened

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual 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

locking

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.

User concepts

Access control

Windows-Profile

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and organizations can be defined via Rockset console

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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

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1 April 2022, Datanami

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

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

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2 September 2019, CNX Software

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