DBMS > H2GIS vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. OpenSearch vs. Sphinx

System Properties Comparison H2GIS vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. OpenSearch vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

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

Globally distributed, horizontally scalable, multi-model database service

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

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

Primary database model

Spatial DBMS

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Secondary database models

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

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	16.03
Rank	#37	Overall
	#4	Search engines

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.h2gis.org

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

azure.microsoft.com/services/cosmos-db

github.com/opensearch-project
opensearch.org

sphinxsearch.com

Technical documentation

www.h2gis.org/docs/home

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

learn.microsoft.com/azure/cosmos-db

opensearch.org/docs/latest

sphinxsearch.com/docs

Developer

CNRS

Microsoft

Amazon Web Services

Sphinx Technologies Inc.

Initial release

2013

2015

2014

2021

2001

Current release

2.5.0, January 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

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.

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Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

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

Java API
RESTful HTTP/JSON API

Proprietary protocol

Supported programming languages

Java

C#
Java
JavaScript
Python

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

based on H2

JavaScript

yes

Triggers

yes

JavaScript

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

yes

none

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

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

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

based on H2

yes

using Azure authentication

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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