DBMS > Graphite vs. KeyDB vs. SiteWhere vs. VelocityDB

System Properties Comparison Graphite vs. KeyDB vs. SiteWhere vs. VelocityDB

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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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

M2M integration platform for persisting/querying time series data

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Time Series DBMS

Key-value store

Time Series DBMS

Graph DBMS
Object oriented DBMS

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

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

github.com/graphite-project/graphite-web

github.com/Snapchat/KeyDB
keydb.dev

github.com/sitewhere/sitewhere

velocitydb.com

Technical documentation

graphite.readthedocs.io

docs.keydb.dev

sitewhere1.sitewhere.io/index.html

velocitydb.com/UserGuide

Developer

Chris Davis

EQ Alpha Technology Ltd.

SiteWhere

VelocityDB Inc

Initial release

2006

2019

2010

2011

Current release

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD-3

Open Source

Common Public Attribution License Version 1.0

commercial

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

Python

C++

Java

Server operating systems

Linux
Unix

Linux

Linux
OS X
Windows

Any that supports .NET

Data scheme

yes

schema-free

predefined scheme

yes

Typing

predefined data types such as float or date

Numeric data only

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

APIs and other access methods

HTTP API
Sockets

Proprietary protocol

RESP - REdis Serialization Protoco

HTTP REST

.Net

Supported programming languages

JavaScript (Node.js)
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

.Net

Server-side scripts

Stored procedures

Lua

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

User concepts

Access control

simple password-based access control and ACL

Users with fine-grained authorization concept

Based on Windows Authentication

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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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Recent citations in the news

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