DBMS > Drizzle vs. Newts vs. Snowflake vs. Yanza

System Properties Comparison Drizzle vs. Newts vs. Snowflake vs. Yanza

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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.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Time Series DBMS based on Cassandra

Cloud-based data warehousing service for structured and semi-structured data

Time Series DBMS for IoT Applications

Primary database model

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

opennms.github.io/newts

www.snowflake.com

yanza.com

Technical documentation

github.com/OpenNMS/newts/wiki

docs.snowflake.net/manuals/index.html

Developer

Drizzle project, originally started by Brian Aker

OpenNMS Group

Snowflake Computing Inc.

Yanza

Initial release

2008

2014

2015

Current release

7.2.4, September 2012

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Windows

hosted

Windows

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

HTTP REST
Java API

CLI Client
JDBC
ODBC

HTTP API

Supported programming languages

C
C++
Java
PHP

Java

JavaScript (Node.js)
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

similar concept for controling cloud resources

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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 with fine-grained authorization concept, user roles and pluggable authentication

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