DBMS > Bangdb vs. FatDB vs. Hyprcubd vs. SQream DB

System Properties Comparison Bangdb vs. FatDB vs. Hyprcubd vs. SQream DB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Serverless Time Series DBMS

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store
Key-value store

Time Series DBMS

Relational 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	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

bangdb.com

hyprcubd.com (offline)

sqream.com

Technical documentation

docs.bangdb.com

docs.sqream.com

Developer

Sachin Sinha, BangDB

FatCloud

Hyprcubd, Inc.

SQream Technologies

Initial release

2012

2017

Current release

BangDB 2.0, October 2021

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

BSD 3

commercial

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++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Windows

hosted

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

time, int, uint, float, string

yes, ANSI Standard SQL Types

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

Via inetgration in SQL Server

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

gRPC (https)

.Net
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

user defined functions in Python

Triggers

yes, Notifications (with Streaming only)

yes

via applications

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 and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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, 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

User concepts

Access control

yes (enterprise version only)

Can implement custom security layer via applications

token access

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More resources

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provided by Google News

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