DBMS > Adabas vs. Bangdb vs. Hive vs. Quasardb

System Properties Comparison Adabas vs. Bangdb vs. Hive vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

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

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

Distributed, high-performance timeseries database

Primary database model

Multivalue DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	4.78
Rank	#81	Overall
	#1	Multivalue DBMS

Score	0.04
Rank	#332	Overall
	#45	Document stores
	#34	Graph DBMS
	#29	Time Series DBMS

Score	81.61
Rank	#17	Overall
	#11	Relational DBMS

Score	0.11
Rank	#310	Overall
	#28	Time Series DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

bangdb.com

hive.apache.org

quasardb.net

Technical documentation

bangdb.com/developer

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

doc.quasar.ai/master

Developer

Software AG

Sachin Sinha, BangDB

Apache Software Foundation

initially developed by Facebook

quasardb

Initial release

1971

2012

2009

Current release

BangDB 2.0, October 2021

3.1.2, August 2019

3.13.3, April 2022

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

Apache Version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

All OS with a Java VM

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

integer and binary

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

with tags

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL like support with command line tool

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
Thrift

HTTP API

Supported programming languages

Natural

C
C#
C++
Java
Python

C++
Java
PHP
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

in Natural

yes

user defined functions and integration of map-reduce

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

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

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

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

selectable replication factor

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

by using LevelDB

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

Transient mode

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

yes (enterprise version only)

Access rights for users, groups and roles

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

Specific characteristics

BangDB is a converged NoSql database platform which natively integrated streaming,...
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High-performance , high-speed, fully integrated timeseries database Seamlessly combines...
» more

Competitive advantages

Converged Platform to break silos for higher scale and performance BangDB is a novel...
» more

High performance in a cost-effective small package Real-time results for even large...
» more

Typical application scenarios

IOT and time series data monitoring Devops, servers, network monitoring Real-Time...
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Tick database Predictive maintenance Pre-deal checks Large scale monitoring
» more

Key customers

Cisco, Accenture, Opera, Airpay, CtrlS, makemytrip, wine central, over 150 SaaS customers
» more

Large EU investment banks US based hedge funds Orolia Tellmeplus
» more

Market metrics

BangDB is one of the fastest databases in the marke with over 2X performance over...
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Has been running in very demanding production environments since 2013 Rapid adoption...
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Licensing and pricing models

BangDB community and enterprise model. Details at https://bangdb.com/pricing/
» more

Community edition limited to 2 nodes and 16 GiB of storage per node available for...
» more

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