DBMS > Apache IoTDB vs. Dgraph vs. Microsoft Azure SQL Database vs. MySQL vs. Oracle Coherence

System Properties Comparison Apache IoTDB vs. Dgraph vs. Microsoft Azure SQL Database vs. MySQL vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Distributed and scalable native Graph DBMS

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

Widely used open source RDBMS

Oracles in-memory data grid solution

Primary database model

Time Series DBMS

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

iotdb.apache.org

dgraph.io

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

www.mysql.com

www.oracle.com/java/coherence

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

dgraph.io/docs

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

dev.mysql.com/doc

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

Developer

Apache Software Foundation

Dgraph Labs, Inc.

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Initial release

2018

2016

2010

1995

2007

Current release

1.1.0, April 2023

V12

8.4.0, April 2024

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

C++

C and C++

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Data scheme

yes

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

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
Native API

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

JCache
JPA
RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

.Net
C#
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
C++
Java

Server-side scripts

Stored procedures

yes

Transact SQL

yes

proprietary syntax

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

yes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Synchronous replication via Raft

yes, with always 3 replicas available

Multi-source replication
Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

configurable

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

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

yes

Planned for future releases

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

authentification to access the cache via certificates or http basic authentication

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