DBMS > BigObject vs. Greenplum vs. PlanetScale vs. Postgres-XL

System Properties Comparison BigObject vs. Greenplum vs. PlanetScale vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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.

Scalable, distributed, serverless MySQL database platform built on top of Vitess

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

Technical documentation

docs.bigobject.io

docs.greenplum.org

planetscale.com/docs

www.postgres-xl.org/documentation

Developer

BigObject, Inc.

Pivotal Software Inc.

PlanetScale

Initial release

2015

2005

2020

2014

since 2012, originally named StormDB

Current release

7.0.0, September 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Docker
Linux
macOS

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

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

distributed, parallel query execution

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

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

Supported programming languages

C
Java
Perl
Python
R

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

ACID at shard level

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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More resources

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