DBMS > Drizzle vs. Lovefield vs. OpenTSDB vs. Splunk

System Properties Comparison Drizzle vs. Lovefield vs. OpenTSDB vs. Splunk

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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.

Embeddable relational database for web apps written in pure JavaScript

Scalable Time Series DBMS based on HBase

Analytics Platform for Big Data

Primary database model

Relational DBMS

Time Series DBMS

Search engine

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

google.github.io/lovefield

opentsdb.net

www.splunk.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

opentsdb.net/docs/build/html/index.html

docs.splunk.com/Documentation/Splunk

Developer

Drizzle project, originally started by Brian Aker

Google

currently maintained by Yahoo and other contributors

Splunk Inc.

Initial release

2008

2014

2011

2003

Current release

7.2.4, September 2012

2.1.12, February 2017

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

LGPL

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++

JavaScript

Java

Server operating systems

FreeBSD
Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

SQL-like query language

via JavaScript builder pattern

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC

HTTP API
Telnet API

HTTP REST

Supported programming languages

C
C++
Java
PHP

JavaScript

Erlang
Go
Java
Python
R
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

selectable replication factor

based on HBase

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles

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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

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Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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Recent citations in the news

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

A real-time processing revival - O'Reilly Radar
2 April 2015, O'Reilly Radar

provided by Google News

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