DBMS > Bangdb vs. Greenplum vs. Hive vs. Sadas Engine

System Properties Comparison Bangdb vs. Greenplum vs. Hive vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

Technical documentation

docs.bangdb.com

docs.greenplum.org

cwiki.apache.org/confluence/display/Hive/Home

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Sachin Sinha, BangDB

Pivotal Software Inc.

Apache Software Foundation

initially developed by Facebook

SADAS s.r.l.

Initial release

2012

2005

2012

2006

Current release

BangDB 2.0, October 2021

7.0.0, September 2023

3.1.3, April 2022

8.0

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

AIX
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
Thrift

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C#
C++
Java
Python

C
Java
Perl
Python
R

C++
Java
PHP
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

managed by 'Learn by Usage'

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

Access rights for users, groups and roles according to SQL-standard

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