DBMS > Bangdb vs. Cachelot.io vs. Cubrid vs. HugeGraph vs. Sphinx

System Properties Comparison Bangdb vs. Cachelot.io vs. Cubrid vs. HugeGraph vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

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

In-memory caching system

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A fast-speed and highly-scalable Graph DBMS

Open source search engine for searching in data from different sources, e.g. relational databases

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

Score	0.00
Rank	#354	Overall
	#54	Key-value stores

Score	1.20
Rank	#160	Overall
	#76	Relational DBMS

Score	0.22
Rank	#286	Overall
	#22	Graph DBMS

Score	6.72
Rank	#63	Overall
	#7	Search engines

Website

bangdb.com

cachelot.io

cubrid.com (korean)
cubrid.org (english)

github.com/hugegraph

sphinxsearch.com

Technical documentation

bangdb.com/developer

cubrid.org/manuals

hugegraph.github.io/hugegraph-doc

sphinxsearch.com/docs

Developer

Sachin Sinha, BangDB

CUBRID Corporation, CUBRID Foundation

Baidu

Sphinx Technologies Inc.

Initial release

2012

2015

2008

2018

2001

Current release

BangDB 2.0, October 2021

11.0, January 2021

0.9

3.4.1, July 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Simplified BSD License

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

C++

C, C++, Java

Java

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
Windows

Linux
macOS
Unix

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

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

also supports composite index and range index

yes

full-text index on all search fields

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language (SphinxQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Memcached protocol

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP API
TinkerPop Gremlin

Proprietary protocol

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Groovy
Java
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

asynchronous Gremlin script jobs

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

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

The original contents of fields are not stored in the Sphinx index.

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)

fine grained access rights according to SQL-standard

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

BangDB is a converged NoSql database platform which natively integrated streaming,...
» more

Competitive advantages

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

Typical application scenarios

IOT and time series data monitoring Devops, servers, network monitoring Real-Time...
» more

Key customers

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

Market metrics

BangDB is one of the fastest databases in the marke with over 2X performance over...
» more

Licensing and pricing models

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

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

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