DBMS > Greenplum vs. JanusGraph vs. Machbase Neo vs. Postgres-XL

System Properties Comparison Greenplum vs. JanusGraph vs. Machbase Neo vs. Postgres-XL

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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.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

Technical documentation

docs.greenplum.org

docs.janusgraph.org

machbase.com/dbms

www.postgres-xl.org/documentation

Developer

Pivotal Software Inc.

Linux Foundation; originally developed as Titan by Aurelius

Machbase

Initial release

2005

2017

2013

2014

since 2012, originally named StormDB

Current release

7.0.0, September 2023

0.6.3, February 2023

V8.0, August 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

free test version 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

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
macOS
Windows

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

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

Supported programming languages

C
Java
Perl
Python
R

Clojure
Java
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.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

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
9 September 2019, AWS Blog

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

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

Greenplum 6 ventures outside the analytic box
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

provided by Google News

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

Database Deep Dives: JanusGraph
8 August 2019, IBM

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
30 July 2020, Towards Data Science

Compose for JanusGraph arrives on Bluemix
15 September 2017, IBM

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

provided by Google News

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