DBMS > Greenplum vs. PlanetScale vs. Stardog vs. VelocityDB

System Properties Comparison Greenplum vs. PlanetScale vs. Stardog vs. VelocityDB

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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.

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS
RDF store

Graph DBMS
Object oriented 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	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

Technical documentation

docs.greenplum.org

planetscale.com/docs

docs.stardog.com

velocitydb.com/UserGuide

Developer

Pivotal Software Inc.

PlanetScale

Stardog-Union

VelocityDB Inc

Initial release

2005

2020

2010

2011

Current release

7.0.0, September 2023

7.3.0, May 2020

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Java

Server operating systems

Linux

Docker
Linux
macOS

Linux
macOS
Windows

Any that supports .NET

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

.Net

Supported programming languages

C
Java
Perl
Python
R

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net

Server-side scripts

Stored procedures

yes

proprietary syntax

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication in HA-Cluster

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 across shards
Immediate Consistency within a shard

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

Based on Windows Authentication

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More resources

Recent citations in the news

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
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RSA: EMC integrates Hadoop with Greenplum database
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Greenplum 6 ventures outside the analytic box | ZDNET
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