DBMS > Graphite vs. JanusGraph vs. NCache vs. SQLite vs. VelocityDB

System Properties Comparison Graphite vs. JanusGraph vs. NCache vs. SQLite vs. VelocityDB

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Open-Source and Enterprise in-memory Key-Value Store

Widely used embeddable, in-process RDBMS

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

Primary database model

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

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

Website

github.com/graphite-project/graphite-web

janusgraph.org

www.alachisoft.com/ncache

www.sqlite.org

velocitydb.com

Technical documentation

graphite.readthedocs.io

docs.janusgraph.org

www.alachisoft.com/resources/docs

www.sqlite.org/docs.html

velocitydb.com/UserGuide

Developer

Chris Davis

Linux Foundation; originally developed as Titan by Aurelius

Alachisoft

Dwayne Richard Hipp

VelocityDB Inc

Initial release

2006

2017

2005

2000

2011

Current release

0.6.3, February 2023

5.3.3, April 2024

3.45.3 (15 April 2024), April 2024

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Enterprise Edition available

Open Source

Public Domain

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

Java

C#, .NET, .NET Core, Java

Server operating systems

Linux
Unix

Linux
OS X
Unix
Windows

Linux
Windows

server-less

Any that supports .NET

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

Numeric data only

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API
Sockets

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

IDistributedCache
JCache
LINQ
Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net

Supported programming languages

JavaScript (Node.js)
Python

Clojure
Java
Python

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net

Server-side scripts

Stored procedures

yes

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Based on Windows Authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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