DBMS > Dgraph vs. EsgynDB vs. InterSystems Caché vs. Microsoft Azure Cosmos DB vs. SiteWhere

System Properties Comparison Dgraph vs. EsgynDB vs. InterSystems Caché vs. Microsoft Azure Cosmos DB vs. SiteWhere

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Distributed and scalable native Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A multi-model DBMS and application server

Globally distributed, horizontally scalable, multi-model database service

M2M integration platform for persisting/querying time series data

Primary database model

Graph DBMS

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

dgraph.io

www.esgyn.cn

www.intersystems.com/products/cache

azure.microsoft.com/services/cosmos-db

github.com/sitewhere/sitewhere

Technical documentation

dgraph.io/docs

docs.intersystems.com

learn.microsoft.com/azure/cosmos-db

sitewhere1.sitewhere.io/index.html

Developer

Dgraph Labs, Inc.

Esgyn

InterSystems

Microsoft

SiteWhere

Initial release

2016

2015

1997

2014

2010

Current release

2018.1.4, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

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

Java

Server operating systems

Linux
OS X
Windows

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

depending on used data model

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

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

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

Source-replica replication

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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