DBMS > Greenplum vs. JanusGraph vs. OrigoDB vs. SiteWhere vs. Teradata Aster

System Properties Comparison Greenplum vs. JanusGraph vs. OrigoDB vs. SiteWhere vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed 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.

A Graph DBMS optimized for distributed clusters

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

A fully ACID in-memory object graph database

M2M integration platform for persisting/querying time series data

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Graph DBMS

Document store
Object oriented DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

greenplum.org

janusgraph.org

origodb.com

github.com/sitewhere/sitewhere

Technical documentation

docs.greenplum.org

docs.janusgraph.org

origodb.com/docs

sitewhere1.sitewhere.io/index.html

Developer

Pivotal Software Inc.

Linux Foundation; originally developed as Titan by Aurelius

Robert Friberg et al

SiteWhere

Teradata

Initial release

2005

2017

2009

under the name LiveDB

2010

2005

Current release

7.0.0, September 2023

1.0.0, October 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

commercial

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
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

predefined scheme

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

.NET Client API
HTTP API
LINQ

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
Java
Perl
Python
R

Clojure
Java
Python

.Net

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

R packages

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

horizontal partitioning

client side managed; servers are not synchronized

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

selectable replication factor

based on HBase

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

depending on model

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

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

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

User authentification and security via Rexster Graph Server

Role based authorization

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Chapter 1. Introducing the Greenplum Database
6 December 2018, O'Reilly Media

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

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

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

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13 January 2017, Datanami

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3 October 2019, The New Stack

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
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SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

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9 March 2023, H2S Media

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Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Teradata Integrates Big Data Analytic Architecture
22 October 2012, PR Newswire

An American Dream Story, With A Silicon Valley Twist
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Gartner, IBM, Teradata make Big Data announcements
17 October 2012, ZDNet

provided by Google News

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