DBMS > Lovefield vs. OpenTSDB vs. searchxml vs. Splunk

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

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Scalable Time Series DBMS based on HBase

DBMS for structured and unstructured content wrapped with an application server

Analytics Platform for Big Data

Primary database model

Relational DBMS

Time Series DBMS

Native XML DBMS
Search engine

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	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

google.github.io/lovefield

opentsdb.net

www.searchxml.net/category/products

www.splunk.com

Technical documentation

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

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

www.searchxml.net/support/handouts

docs.splunk.com/Documentation/Splunk

Developer

Google

currently maintained by Yahoo and other contributors

informationpartners gmbh

Splunk Inc.

Initial release

2014

2011

2015

2003

Current release

2.1.12, February 2017

1.0

License

Commercial or Open Source

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

JavaScript

Java

C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Linux
Windows

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

SQL-like query language

via JavaScript builder pattern

Splunk Search Processing Language for search commands

APIs and other access methods

HTTP API
Telnet API

RESTful HTTP API
WebDAV
XQuery
XSLT

HTTP REST

Supported programming languages

JavaScript

Erlang
Go
Java
Python
R
Ruby

C++

most other programming languages supported via APIs

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

on the application server

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

yes

sychronisation to multiple collections

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

multiple readers, single writer

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 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

Domain, group and role-based access control at the document level and for application services

Access rights for users and roles

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More resources

DB-Engines blog posts

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

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

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

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

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

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

provided by Google News

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