DBMS > Greenplum vs. LevelDB vs. OrientDB

System Properties Comparison Greenplum vs. LevelDB vs. OrientDB

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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.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	9.23
Rank	#47	Overall
	#30	Relational DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	3.27
Rank	#97	Overall
	#16	Document stores
	#6	Graph DBMS
	#15	Key-value stores

Website

greenplum.org

github.com/google/leveldb

orientdb.org

Technical documentation

docs.greenplum.org

github.com/google/leveldb/blob/main/doc/index.md

www.orientdb.com/docs/last/index.html

Developer

Pivotal Software Inc.

Google

OrientDB LTD; CallidusCloud; SAP

Initial release

2005

2011

2010

Current release

7.0.0, September 2023

1.23, February 2021

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache version 2

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++

Java

Server operating systems

Linux

Illumos
Linux
OS X
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

C
Java
Perl
Python
R

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Java, Javascript

Triggers

yes

Hooks

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

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

with automatic compression on writes

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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