DBMS > Bangdb vs. Hive vs. HyperSQL vs. NCache vs. SWC-DB

System Properties Comparison Bangdb vs. Hive vs. HyperSQL vs. NCache vs. SWC-DB

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Open-Source and Enterprise in-memory Key-Value Store

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

Wide column store

Secondary database models

Spatial DBMS

Document store
Search engine

Using distributed Lucene

Time Series DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

bangdb.com

hive.apache.org

hsqldb.org

www.alachisoft.com/ncache

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.bangdb.com

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

hsqldb.org/web/hsqlDocsFrame.html

www.alachisoft.com/resources/docs

Developer

Sachin Sinha, BangDB

Apache Software Foundation

initially developed by Facebook

Alachisoft

Alex Kashirin

Initial release

2012

2001

2005

2020

Current release

BangDB 2.0, October 2021

3.1.3, April 2022

2.7.2, June 2023

5.3.3, April 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2

Open Source

based on BSD license

Open Source

Enterprise Edition available

Open Source

GPL V3

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#, .NET, .NET Core, Java

C++

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
Thrift

HTTP API

JDBC via HTTP
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

Proprietary protocol
Thrift

Supported programming languages

C
C#
C++
Java
Python

C++
Java
PHP
Python

All languages supporting JDBC/ODBC
Java

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

C++

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java, SQL

support for stored procedures with SQL-Server CLR

Triggers

yes, Notifications (with Streaming only)

yes

Notifications

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

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

none

yes, with selectable consistency level

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

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

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

User concepts

Access control

yes (enterprise version only)

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
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Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
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Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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