DBMS > Drizzle vs. FatDB vs. Newts vs. Quasardb vs. Splunk

System Properties Comparison Drizzle vs. FatDB vs. Newts vs. Quasardb vs. Splunk

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.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Analytics Platform for Big Data

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Search engine

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

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

opennms.github.io/newts

quasar.ai

www.splunk.com

Technical documentation

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

docs.splunk.com/Documentation/Splunk

Developer

Drizzle project, originally started by Brian Aker

FatCloud

OpenNMS Group

quasardb

Splunk Inc.

Initial release

2008

2012

2014

2009

2003

Current release

7.2.4, September 2012

3.14.1, January 2024

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache 2.0

commercial

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

commercial

Limited free edition and free developer edition available

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++

Server operating systems

FreeBSD
Linux
OS X

Windows

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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.

yes

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

with proprietary extensions

Via inetgration in SQL Server

SQL-like query language

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP REST
Java API

HTTP API

HTTP REST

Supported programming languages

C
C++
Java
PHP

Java

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

via applications

yes

Triggers

hooks for callbacks inside the server can be used.

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Can implement custom security layer via applications

Cryptographically strong user authentication and audit trail

Access rights for users and roles

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More resources

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