DBMS > Greenplum vs. JaguarDB vs. Machbase Neo vs. Microsoft Azure Table Storage

System Properties Comparison Greenplum vs. JaguarDB vs. Machbase Neo vs. Microsoft Azure Table Storage

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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.

Performant, highly scalable DBMS for AI and IoT applications

TimeSeries DBMS for AIoT and BigData

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Time Series DBMS

Wide column store

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

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

greenplum.org

www.jaguardb.com

machbase.com

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

docs.greenplum.org

www.jaguardb.com/support.html

machbase.com/dbms

Developer

Pivotal Software Inc.

DataJaguar, Inc.

Machbase

Microsoft

Initial release

2005

2015

2013

2012

Current release

7.0.0, September 2023

3.3 July 2023

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3.0

commercial

free test version available

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

C++

the server part. Clients available in other languages

Server operating systems

Linux

Linux
macOS
Windows

hosted

Data scheme

yes

schema-free

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

selectable replication factor

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

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

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

rights management via user accounts

simple password-based access control

Access rights based on private key authentication or shared access signatures

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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, O'Reilly Media

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

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

EMC Introduces Breakthrough 'Big Data' Computing System
13 October 2010, PR Newswire

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Working with Azure to Use and Manage Data Lakes
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How to use Azure Table storage in .Net
14 January 2019, InfoWorld

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

Inside Azure File Storage
7 October 2015, Microsoft

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