DBMS > Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Sphinx vs. TypeDB vs. VoltDB

System Properties Comparison Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Sphinx vs. TypeDB vs. VoltDB

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

Open source search engine for searching in data from different sources, e.g. relational databases

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Relational DBMS

Secondary database models

Vector DBMS

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	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

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

azure.microsoft.com/services/cosmos-db

sphinxsearch.com

typedb.com

www.voltdb.com

Technical documentation

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

learn.microsoft.com/azure/cosmos-db

sphinxsearch.com/docs

typedb.com/docs

docs.voltdb.com

Developer

Microsoft

Sphinx Technologies Inc.

Vaticle

VoltDB Inc.

Initial release

2015

2014

2001

2016

2010

Current release

3.5.1, February 2023

2.26.3, January 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2, commercial licence available

Open Source

GPL Version 3, commercial licenses available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, C++

Server operating systems

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
OS X

for development

Data scheme

yes

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API

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

Proprietary protocol

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C#
Java
JavaScript
Python

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Java

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

by using Cassandra

Sharding

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

Multi-source replication

by using Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

by using Apache Kafka and Apache Zookeeper

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

substituted by the relationship feature

FOREIGN KEY constraints are not supported

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

using Azure authentication

Access rights can be defined down to the item level

yes

at REST API level; other APIs in progress

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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