DBMS > BigObject vs. GBase vs. Greenplum vs. Infobright vs. Qdrant

System Properties Comparison BigObject vs. GBase vs. Greenplum vs. Infobright vs. Qdrant

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

A high-performance vector database with neural network or semantic-based matching

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	1.28
Rank	#167	Overall
	#8	Vector DBMS

Website

bigobject.io

www.gbase.cn

greenplum.org

ignitetech.com/softwarelibrary/infobrightdb

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.bigobject.io

docs.greenplum.org

qdrant.tech/documentation

Developer

BigObject, Inc.

General Data Technology Co., Ltd.

Pivotal Software Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Qdrant

Initial release

2015

2004

2005

2021

Current release

GBase 8a, GBase 8s, GBase 8c

7.0.0, September 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

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 Version 2.0

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, Java, Python

Rust

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

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL-like DML and DDL statements

Standard with numerous extensions

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Lua

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

Collection-level 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, tunable 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

yes

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Key-based authentication

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More resources

Recent citations in the news

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, oreilly.com

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
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RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box | ZDNET
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