DBMS > Blueflood vs. Google BigQuery vs. Greenplum vs. PostGIS

System Properties Comparison Blueflood vs. Google BigQuery vs. Greenplum vs. PostGIS

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Large scale data warehouse service with append-only tables

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.

Spatial extension of PostgreSQL

Primary database model

Time Series DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

blueflood.io

cloud.google.com/bigquery

greenplum.org

postgis.net

Technical documentation

github.com/rax-maas/blueflood/wiki

cloud.google.com/bigquery/docs

docs.greenplum.org

postgis.net/documentation

Developer

Rackspace

Google

Pivotal Software Inc.

Initial release

2013

2010

2005

Current release

7.0.0, September 2023

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

GPL v2.0

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

Java

Server operating systems

Linux
OS X

hosted

Linux

Data scheme

predefined 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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
Java
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

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.

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.