DBMS > Dgraph vs. GridGain vs. Microsoft Azure SQL Database vs. NuoDB vs. Oracle

System Properties Comparison Dgraph vs. GridGain vs. Microsoft Azure SQL Database vs. NuoDB vs. Oracle

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

GridGain is an in-memory computing platform, built on Apache Ignite

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Widely used RDBMS

Primary database model

Graph DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	1.53
Rank	#155	Overall
	#26	Key-value stores
	#73	Relational DBMS

Score	78.40
Rank	#15	Overall
	#10	Relational DBMS

Score	0.99
Rank	#195	Overall
	#92	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Website

dgraph.io

www.gridgain.com

azure.microsoft.com/en-us/products/azure-sql/database

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

www.oracle.com/database

Technical documentation

dgraph.io/docs

www.gridgain.com/docs/index.html

docs.microsoft.com/en-us/azure/azure-sql

doc.nuodb.com

docs.oracle.com/en/database

Developer

Dgraph Labs, Inc.

GridGain Systems, Inc.

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Oracle

Initial release

2016

2007

2010

2013

1980

Current release

GridGain 8.5.1

V12

23c, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net

C++

C and C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

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

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

APIs and other access methods

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

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

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Transact SQL

Java, SQL

PL/SQL

also stored procedures in Java possible

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

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

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes (replicated cache)

yes, with always 3 replicas available

yes

Managed transparently by NuoDB

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Planned for future releases

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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