DBMS > Dgraph vs. Heroic vs. MySQL vs. NCache vs. NuoDB

System Properties Comparison Dgraph vs. Heroic vs. MySQL vs. NCache vs. NuoDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Widely used open source RDBMS

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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Graph DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

Relational 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	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Website

dgraph.io

github.com/spotify/heroic

www.mysql.com

www.alachisoft.com/ncache

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

dgraph.io/docs

spotify.github.io/heroic

dev.mysql.com/doc

www.alachisoft.com/resources/docs

doc.nuodb.com

Developer

Dgraph Labs, Inc.

Spotify

Oracle

since 2010, originally MySQL AB, then Sun

Alachisoft

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2016

2014

1995

2005

2013

Current release

8.4.0, April 2024

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Enterprise Edition available

commercial

limited edition free

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

Java

C and C++

C#, .NET, .NET Core, Java

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

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

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 Elasticsearch

yes

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.

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

IDistributedCache
JCache
LINQ
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

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

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

Server-side scripts

Stored procedures

yes

proprietary syntax

support for stored procedures with SQL-Server CLR

Java, SQL

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate 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

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

optimistic locking and pessimistic locking

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

MVCC

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Temporary table

User concepts

Access control

Planned for future releases

Users with fine-grained authorization concept

no user groups or roles

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

Standard SQL roles/ privileges, Administrative Users

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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