DBMS > AgensGraph vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. Realm vs. SAP SQL Anywhere

System Properties Comparison AgensGraph vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. Realm vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Graph DBMS
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

bitnine.net/agensgraph

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

realm.io

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

bitnine.net/documentation

learn.microsoft.com/azure/cosmos-db

realm.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Bitnine Global Inc.

Microsoft

Realm, acquired by MongoDB in May 2019

SAP

formerly Sybase

Initial release

2016

2014

2012

2014

1992

Current release

2.1, December 2018

17, July 2015

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

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

Server operating systems

Linux
OS X
Windows

hosted

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

depending on used data model

schema-free

yes

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

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

Cypher Query Language
JDBC

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

RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

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

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

.Net
Java

with Android only
Objective-C
React Native
Swift

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

Server-side scripts

Stored procedures

yes

JavaScript

runs within the applications so server-side scripts are unnecessary

yes, in C/C++, Java, .Net or Perl

Triggers

JavaScript

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

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

optimistic locking

ACID

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

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

yes

fine grained access rights according to SQL-standard

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