DBMS > Bangdb vs. Hive vs. IBM Cloudant vs. Machbase Neo vs. Tkrzw

System Properties Comparison Bangdb vs. Hive vs. IBM Cloudant vs. Machbase Neo vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering based on Apache CouchDB

TimeSeries DBMS for AIoT and BigData

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

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	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

bangdb.com

hive.apache.org

www.ibm.com/products/cloudant

machbase.com

dbmx.net/tkrzw

Technical documentation

docs.bangdb.com

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

cloud.ibm.com/docs/Cloudant

machbase.com/dbms

Developer

Sachin Sinha, BangDB

Apache Software Foundation

initially developed by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Machbase

Mikio Hirabayashi

Initial release

2012

2010

2013

2020

Current release

BangDB 2.0, October 2021

3.1.3, April 2022

V8.0, August 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2

commercial

free test version available

Open Source

Apache Version 2.0

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

C, C++

Java

Erlang

C++

Server operating systems

Linux

All OS with a Java VM

hosted

Linux
macOS
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
Thrift

RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

C
C#
C++
Java
Python

C++
Java
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Optimistic locking

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

volatile and lookup table

yes

using specific database classes

User concepts

Access control

yes (enterprise version only)

Access rights for users, groups and roles

Access rights for users can be defined per database

simple password-based access control

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