DBMS > Greenplum vs. JaguarDB vs. JSqlDb vs. OrigoDB vs. Postgres-XL

System Properties Comparison Greenplum vs. JaguarDB vs. JSqlDb vs. OrigoDB vs. Postgres-XL

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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

JavaScript Query Language Database, stores JavaScript objects and primitives

A fully ACID in-memory object graph database

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

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

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	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

jsqldb.org (offline)

Technical documentation

docs.greenplum.org

www.jaguardb.com/support.html

origodb.com/docs

www.postgres-xl.org/documentation

Developer

Pivotal Software Inc.

DataJaguar, Inc.

Konrad von Backstrom

Robert Friberg et al

Initial release

2005

2015

2018

2009

under the name LiveDB

2014

since 2012, originally named StormDB

Current release

7.0.0, September 2023

3.3 July 2023

0.8, December 2018

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3.0

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

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

Linux
macOS
Windows

Linux
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

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

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

.NET Client API
HTTP API
LINQ

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

JavaScript

.Net

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

Server-side scripts

Stored procedures

yes

functions in JavaScript

yes

user defined functions

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

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

depending on model

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

using RocksDB

yes

Write ahead log

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

Role based authorization

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, oreilly.com

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RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box | ZDNET
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provided by Google News

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