DBMS > Greenplum vs. JaguarDB vs. LeanXcale vs. Microsoft Azure AI Search vs. Postgres-XL

System Properties Comparison Greenplum vs. JaguarDB vs. LeanXcale vs. Microsoft Azure AI Search vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

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.

Performant, highly scalable DBMS for AI and IoT applications

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Key-value store
Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Vector DBMS

Document store
Spatial DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

greenplum.org

www.jaguardb.com

www.leanxcale.com

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

www.postgres-xl.org

Technical documentation

docs.greenplum.org

www.jaguardb.com/support.html

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

www.postgres-xl.org/documentation

Developer

Pivotal Software Inc.

DataJaguar, Inc.

LeanXcale

Microsoft

Initial release

2005

2015

2014

since 2012, originally named StormDB

Current release

7.0.0, September 2023

3.3 July 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3.0

commercial

Open Source

Mozilla public license

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++

the server part. Clients available in other languages

Server operating systems

Linux

hosted

Linux
macOS

Data scheme

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

through Apache Derby

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
Java
Perl
Python
R

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
Java
Scala

C#
Java
JavaScript
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

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

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

MVCC

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

fine grained access rights according to SQL-standard

rights management via user accounts

yes

using Azure authentication

fine grained access rights according to SQL-standard

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More resources

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