DBMS > Cachelot.io vs. EsgynDB vs. Greenplum vs. Lovefield vs. Microsoft Azure AI Search

System Properties Comparison Cachelot.io vs. EsgynDB vs. Greenplum vs. Lovefield vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Key-value store

Relational DBMS

Search engine

Secondary database models

Document store
Spatial DBMS

Vector DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Website

cachelot.io

www.esgyn.cn

greenplum.org

google.github.io/lovefield

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

Technical documentation

docs.greenplum.org

github.com/google/lovefield/blob/master/docs/spec_index.md

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

Developer

Esgyn

Pivotal Software Inc.

Google

Microsoft

Initial release

2015

2005

2014

2015

Current release

7.0.0, September 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

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++

C++, Java

JavaScript

Server operating systems

FreeBSD
Linux
OS X

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

schema-free

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Memcached protocol

ADO.NET
JDBC
ODBC

JDBC
ODBC

RESTful HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Perl
Python
R

JavaScript

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

Source-replica replication

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using Azure authentication

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