DBMS > Graphite vs. GridDB vs. LokiJS vs. MySQL vs. Sphinx

System Properties Comparison Graphite vs. GridDB vs. LokiJS vs. MySQL vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Scalable in-memory time series database optimized for IoT and Big Data

In-memory JavaScript DBMS

Widely used open source RDBMS

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

Primary database model

Time Series DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Search engine

Secondary database models

Key-value store
Relational DBMS

Document store
Spatial DBMS

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

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

github.com/graphite-project/graphite-web

griddb.net

github.com/techfort/LokiJS

www.mysql.com

sphinxsearch.com

Technical documentation

graphite.readthedocs.io

docs.griddb.net

techfort.github.io/LokiJS

dev.mysql.com/doc

sphinxsearch.com/docs

Developer

Chris Davis

Toshiba Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

Initial release

2006

2013

2014

1995

2001

Current release

5.1, August 2022

8.4.0, April 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

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Implementation language

Python

C++

JavaScript

C and C++

C++

Server operating systems

Linux
Unix

Linux

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

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

yes

numerical, string, blob, geometry, boolean, timestamp

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

via views

yes

full-text index on all search fields

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP API
Sockets

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JavaScript API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

Supported programming languages

JavaScript (Node.js)
Python

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency within container, eventual consistency across containers

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID at container level

atomic operations within a single collection possible

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

User concepts

Access control

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.