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

System Properties Comparison Greenplum vs. LevelDB 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.

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

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	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

greenplum.org

github.com/google/leveldb

machbase.com

www.postgres-xl.org

Technical documentation

docs.greenplum.org

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

machbase.com/dbms

www.postgres-xl.org/documentation

Developer

Pivotal Software Inc.

Google

Machbase

Initial release

2005

2011

2013

2014

since 2012, originally named StormDB

Current release

7.0.0, September 2023

1.23, February 2021

V8.0, August 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

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

C++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux
macOS
Windows

Linux
macOS

Data scheme

yes

schema-free

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

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

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.

yes

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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