DBMS > Bangdb vs. Databricks vs. Hyprcubd vs. MySQL

System Properties Comparison Bangdb vs. Databricks vs. Hyprcubd vs. MySQL

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Editorial information provided by DB-Engines

Name

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Serverless Time Series DBMS

Widely used open source RDBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

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	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

bangdb.com

www.databricks.com

hyprcubd.com (offline)

www.mysql.com

Technical documentation

docs.bangdb.com

docs.databricks.com

dev.mysql.com/doc

Developer

Sachin Sinha, BangDB

Databricks

Hyprcubd, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

2013

1995

Current release

BangDB 2.0, October 2021

8.4.0, April 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++

C and C++

Server operating systems

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, 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

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

with Databricks SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

gRPC (https)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Java
Python

Python
R
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

proprietary syntax

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

table locks or row locks depending on storage engine

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)

token access

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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