DBMS > EsgynDB vs. Microsoft Azure AI Search vs. Pinecone vs. Realm vs. ToroDB

System Properties Comparison EsgynDB vs. Microsoft Azure AI Search vs. Pinecone vs. Realm vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

A managed, cloud-native vector database

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Vector DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	5.75
Rank	#58	Overall
	#7	Search engines

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Website

www.esgyn.cn

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

www.pinecone.io

realm.io

github.com/torodb/server

Technical documentation

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

docs.pinecone.io/docs/overview

realm.io/docs

Developer

Esgyn

Microsoft

Pinecone Systems, Inc

Realm, acquired by MongoDB in May 2019

8Kdata

Initial release

2015

2019

2014

2016

Current release

License

Commercial or Open Source

commercial

Open Source

AGPL-V3

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

Server operating systems

Linux

hosted

Android
Backend: server-less
iOS
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

yes

string, integer, double, boolean, date, object_id

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

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C#
Java
JavaScript
Python

Python

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

Java Stored Procedures

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

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

Multi-source replication between multi datacenters

yes

Implicit feature of the cloud service

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using Azure authentication

yes

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

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

provided by Google News

Using the Pinecone vector database in .NET
12 September 2024, InfoWorld

Pinecone serverless goes multicloud as vector database market heats up
27 August 2024, VentureBeat

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

Pinecone vector database available on AWS, Azure, and Google clouds
27 August 2024, Blocks & Files

Pinecone launches serverless vector database on Azure, GCP
27 August 2024, TechTarget

provided by Google News

Is Swift the Future of Server-side Development?
12 September 2017, Solutions Review

Just How Powerful Is Wikipedia?
4 September 2008, SitePoint

Java Synthetic Methods — What are these ?
27 February 2021, DataDrivenInvestor

Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

provided by Google News

Share this page