DBMS > Dgraph vs. Drizzle vs. Microsoft Azure SQL Database vs. Oracle Coherence

System Properties Comparison Dgraph vs. Drizzle vs. Microsoft Azure SQL Database vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Distributed and scalable native Graph DBMS

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Oracles in-memory data grid solution

Primary database model

Graph DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	78.40
Rank	#15	Overall
	#10	Relational DBMS

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Website

dgraph.io

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

www.oracle.com/java/coherence

Technical documentation

dgraph.io/docs

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

docs.oracle.com/en/middleware/standalone/coherence

Developer

Dgraph Labs, Inc.

Drizzle project, originally started by Brian Aker

Microsoft

Oracle

Initial release

2016

2008

2010

2007

Current release

7.2.4, September 2012

V12

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

commercial

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

C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

hosted

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

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

yes

with proprietary extensions

yes

APIs and other access methods

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

JDBC

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

Supported programming languages

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

C
C++
Java
PHP

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

.Net
C++
Java

Server-side scripts

Stored procedures

Transact SQL

Triggers

hooks for callbacks inside the server can be used.

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication
Source-replica replication

yes, with always 3 replicas available

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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