DBMS > JanusGraph vs. MySQL vs. NCache vs. Qdrant

System Properties Comparison JanusGraph vs. MySQL vs. NCache vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

A Graph DBMS optimized for distributed clusters

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

Widely used open source RDBMS

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

A high-performance vector database with neural network or semantic-based matching

Primary database model

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

Vector DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.91
Rank	#196	Overall
	#29	Key-value stores

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

janusgraph.org

www.mysql.com

www.alachisoft.com/ncache

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.janusgraph.org

dev.mysql.com/doc

www.alachisoft.com/resources/docs

qdrant.tech/documentation

Developer

Linux Foundation; originally developed as Titan by Aurelius

Oracle

since 2010, originally MySQL AB, then Sun

Alachisoft

Qdrant

Initial release

2017

1995

2005

2021

Current release

1.0.0, October 2023

9.0.0, July 2024

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Enterprise Edition available

Open Source

Apache Version 2.0

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

Java

C and C++

C#, .NET, .NET Core, Java

Rust

Server operating systems

Linux
OS X
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

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

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

with proprietary extensions

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

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
Proprietary native API

IDistributedCache
JCache
LINQ
Proprietary native API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

Clojure
Java
Python

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

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

proprietary syntax

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

yes

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

Collection-level replication

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

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

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

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

Key-based 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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