DBMS > Bangdb vs. Cubrid vs. HarperDB vs. JaguarDB vs. Sadas Engine

System Properties Comparison Bangdb vs. Cubrid vs. HarperDB vs. JaguarDB vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Performant, highly scalable DBMS for AI and IoT applications

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Spatial 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	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

bangdb.com

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

www.harperdb.io

www.jaguardb.com

www.sadasengine.com

Technical documentation

docs.bangdb.com

cubrid.org/manuals

docs.harperdb.io/docs

www.jaguardb.com/support.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Sachin Sinha, BangDB

CUBRID Corporation, CUBRID Foundation

HarperDB

DataJaguar, Inc.

SADAS s.r.l.

Initial release

2012

2008

2017

2015

2006

Current release

BangDB 2.0, October 2021

11.0, January 2021

3.1, August 2021

3.3 July 2023

8.0

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

GPL V3.0

commercial

free trial version 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++, Java

Node.js

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

Linux
Windows

Linux
OS X

Linux

AIX
Linux
Windows

Data scheme

schema-free

yes

dynamic schema

yes

Typing

predefined data types such as float or date

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

yes

JSON data types

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

yes

SQL-like data manipulation statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C#
C++
Java
Python

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Custom Functions

since release 3.1

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

A table resides as a whole on one (or more) nodes in a cluster

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

the nodes on which a table resides can be defined

Multi-source replication

none

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

Transaction concepts

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

ACID

Atomic execution of specific operations

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

yes, using LMDB

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

managed by 'Learn by Usage'

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Access rights for users and roles

rights management via user accounts

Access rights for users, groups and roles according to SQL-standard

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