DBMS > Microsoft Azure AI Search vs. ObjectBox vs. Stardog vs. Trafodion

System Properties Comparison Microsoft Azure AI Search vs. ObjectBox vs. Stardog vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Transactional SQL-on-Hadoop DBMS

Primary database model

Search engine

Object oriented DBMS
Vector DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Vector DBMS

Time Series DBMS

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

Score	5.75
Rank	#58	Overall
	#7	Search engines

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

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

github.com/objectbox
objectbox.io

www.stardog.com

trafodion.apache.org

Technical documentation

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

docs.objectbox.io

docs.stardog.com

trafodion.apache.org/documentation.html

Developer

Microsoft

ObjectBox Limited

Stardog-Union

Apache Software Foundation, originally developed by HP

Initial release

2015

2017

2010

2014

Current release

4.0 (May 2024)

7.3.0, May 2020

2.3.0, February 2019

License

Commercial or Open Source

commercial

Bindings are released under Apache 2.0

Apache License 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache 2.0

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 and C++

Java

C++, Java

Server operating systems

hosted

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like 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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

RESTful HTTP API

Proprietary native API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Python

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

Java Stored Procedures

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Data sync between devices allowing occasional connected databases to work completely offline

Multi-source replication in HA-Cluster

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

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

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

yes

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

Announcing updates to Azure AI Search to help organizations build and scale generative AI applications
4 April 2024, azure.microsoft.com

Public Preview of Azure OpenAI and AI Search in-app connectors for Logic Apps (Standard)
2 April 2024, azure.microsoft.com

Boost your AI with Azure's new Phi model, streamlined RAG, and custom generative AI models
22 August 2024, azure.microsoft.com

From code to production: New ways Azure helps you build transformational AI experiences
21 May 2024, azure.microsoft.com

Microsoft boosts Azure AI Search with more storage and support for big RAG apps
5 April 2024, VentureBeat

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