DBMS > Fauna vs. Greenplum vs. InterSystems Caché vs. Microsoft Azure AI Search vs. Microsoft SQL Server

System Properties Comparison Fauna vs. Greenplum vs. InterSystems Caché vs. Microsoft Azure AI Search vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

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.

A multi-model DBMS and application server

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

Microsofts flagship relational DBMS

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store

Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

fauna.com

greenplum.org

www.intersystems.com/products/cache

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

www.microsoft.com/en-us/sql-server

Technical documentation

docs.fauna.com

docs.greenplum.org

docs.intersystems.com

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

learn.microsoft.com/en-US/sql/sql-server

Developer

Fauna, Inc.

Pivotal Software Inc.

InterSystems

Microsoft

Initial release

2014

2005

1997

2015

1989

Current release

7.0.0, September 2023

2018.1.4, May 2020

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++

Server operating systems

hosted

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

hosted

Linux
Windows

Data scheme

schema-free

yes

depending on used data model

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
Java
Perl
Python
R

C#
C++
Java

C#
Java
JavaScript
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

none

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

User concepts

Access control

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

yes

using Azure authentication

fine grained access rights according to SQL-standard

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