DBMS > BigObject vs. Greenplum vs. Infobright vs. KairosDB vs. SQream DB

System Properties Comparison BigObject vs. Greenplum vs. Infobright vs. KairosDB vs. SQream DB

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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Distributed Time Series DBMS based on Cassandra or H2

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational 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	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	9.23
Rank	#47	Overall
	#30	Relational DBMS

Score	1.00
Rank	#193	Overall
	#90	Relational DBMS

Score	0.71
Rank	#230	Overall
	#20	Time Series DBMS

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

bigobject.io

greenplum.org

ignitetech.com/softwarelibrary/infobrightdb

github.com/kairosdb/kairosdb

sqream.com

Technical documentation

Developer

BigObject, Inc.

Pivotal Software Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

SQream Technologies

Initial release

2015

2005

2013

2017

Current release

7.0.0, September 2023

1.2.2, November 2018

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache 2.0

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

C++, CUDA, Haskell, Java, Scala

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

Linux
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Knowledge Grid Technology used instead

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

.Net
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
JavaScript

Node.js
PHP
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

based on Cassandra

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

based on Cassandra

none

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

exploiting MySQL or PostgreSQL frontend capabilities

simple password-based access control

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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, oreilly.com

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 and Greenplum Dress Elephant for IT Parade
8 December 2011, WIRED

provided by Google News

The re-emergence of time-series – O'Reilly
6 April 2013, oreilly.com

provided by Google News

SQream Announces Strategic Integration for Powerful Big Data Analytics with Dataiku
9 February 2024, insideBIGDATA

I SQream, you SQream, we all SQream for … data analytics?
5 October 2023, FierceWireless

SQream Joins Samsung Cloud Platform Ecosystem
26 July 2023, Datanami

GPU data warehouse startup SQream lands $39.4M funding round
24 June 2020, SiliconANGLE News

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

provided by Google News

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