DBMS > Bangdb vs. Lovefield vs. RRDtool vs. Sphinx

System Properties Comparison Bangdb vs. Lovefield vs. RRDtool vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Embeddable relational database for web apps written in pure JavaScript

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1.70
Rank	#136	Overall
	#11	Time Series DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

bangdb.com

google.github.io/lovefield

oss.oetiker.ch/rrdtool

sphinxsearch.com

Technical documentation

docs.bangdb.com

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

oss.oetiker.ch/rrdtool/doc

sphinxsearch.com/docs

Developer

Sachin Sinha, BangDB

Google

Tobias Oetiker

Sphinx Technologies Inc.

Initial release

2012

2014

1999

2001

Current release

BangDB 2.0, October 2021

2.1.12, February 2017

1.8.0, 2022

3.5.1, February 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

Open Source

GPL version 2, commercial licence 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, C++

JavaScript

Implementations in Java (e.g. RRD4J) and C# available

C++

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

HP-UX
Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

full-text index on all search fields

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

via JavaScript builder pattern

SQL-like query language (SphinxQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

in-process shared library
Pipes

Proprietary protocol

Supported programming languages

C
C#
C++
Java
Python

JavaScript

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

none

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, optimistic concurrency control

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes, run db with in-memory only mode

yes

using MemoryDB

yes

User concepts

Access control

yes (enterprise version only)

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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

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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