DBMS > Greenplum vs. HarperDB vs. JaguarDB vs. Oracle vs. Postgres-XL

System Properties Comparison Greenplum vs. HarperDB vs. JaguarDB vs. Oracle 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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Performant, highly scalable DBMS for AI and IoT applications

Widely used RDBMS

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

Primary database model

Relational DBMS

Document store

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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	0.60
Rank	#244	Overall
	#38	Document stores

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

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

greenplum.org

www.harperdb.io

www.jaguardb.com

www.oracle.com/database

www.postgres-xl.org

Technical documentation

docs.greenplum.org

docs.harperdb.io/docs

www.jaguardb.com/support.html

docs.oracle.com/en/database

www.postgres-xl.org/documentation

Developer

Pivotal Software Inc.

HarperDB

DataJaguar, Inc.

Oracle

Initial release

2005

2017

2015

1980

2014

since 2012, originally named StormDB

Current release

7.0.0, September 2023

3.1, August 2021

3.3 July 2023

23c, September 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community edition available

Open Source

GPL V3.0

commercial

restricted free version is available

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

Node.js

C++

the server part. Clients available in other languages

C and C++

Server operating systems

Linux

Linux
OS X

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
macOS

Data scheme

yes

dynamic schema

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL-like data manipulation statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

with proprietary extensions

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

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

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

PL/SQL

also stored procedures in Java possible

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

the nodes on which a table resides can be defined

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

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

Atomic execution of specific operations

ACID

isolation level can be parameterized

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

rights management via user accounts

fine grained access rights according to SQL-standard

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