DBMS > Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. TigerGraph vs. TinkerGraph

System Properties Comparison Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. TigerGraph vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Search-as-a-service for web and mobile app development

Globally distributed, horizontally scalable, multi-model database service

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Graph DBMS

Secondary database models

Vector DBMS

Spatial DBMS

Document store
Spatial DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

azure.microsoft.com/en-us/services/search

azure.microsoft.com/services/cosmos-db

www.postgres-xl.org

www.tigergraph.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

learn.microsoft.com/en-us/azure/search

learn.microsoft.com/azure/cosmos-db

www.postgres-xl.org/documentation

docs.tigergraph.com

Developer

Microsoft

Initial release

2015

2014

since 2012, originally named StormDB

2017

2009

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

Linux
macOS

Linux

Data scheme

yes

schema-free

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

TinkerPop 3

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++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java

Groovy
Java

Server-side scripts

Stored procedures

JavaScript

user defined functions

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

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

none

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

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

using Azure authentication

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Role-based access control

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