DBMS > Microsoft Azure AI Search vs. Microsoft SQL Server vs. SAP HANA vs. SpaceTime vs. Titan

System Properties Comparison Microsoft Azure AI Search vs. Microsoft SQL Server vs. SAP HANA vs. SpaceTime vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

Microsofts flagship relational DBMS

In-memory, column based data store. Available as appliance or cloud service

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Vector DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

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

www.microsoft.com/en-us/sql-server

www.sap.com/products/hana.html

www.mireo.com/spacetime

github.com/thinkaurelius/titan

Technical documentation

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

learn.microsoft.com/en-US/sql/sql-server

help.sap.com/hana

github.com/thinkaurelius/titan/wiki

Developer

Microsoft

SAP

Mireo

Aurelius, owned by DataStax

Initial release

2015

1989

2010

2020

2012

Current release

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

Linux
Windows

Appliance or cloud-service

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

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

A subset of ANSI SQL is implemented

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C#
Java
JavaScript
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
C++
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

Fixed-grid hypercubes

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

yes

Real-time block device replication (DRBD)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

fine grained access rights according to SQL-standard

yes

User authentification and security via Rexster Graph Server

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