DBMS > Bangdb vs. EsgynDB vs. Faircom EDGE vs. SAP HANA vs. TinkerGraph

System Properties Comparison Bangdb vs. EsgynDB vs. Faircom EDGE vs. SAP HANA vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

In-memory, column based data store. Available as appliance or cloud service

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

bangdb.com

www.esgyn.cn

www.faircom.com/products/faircom-edge

www.sap.com/products/hana.html

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.bangdb.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

help.sap.com/hana

Developer

Sachin Sinha, BangDB

Esgyn

FairCom Corporation

SAP

Initial release

2012

2015

1979

2010

2009

Current release

BangDB 2.0, October 2021

V3, October 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

Restricted, free version available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++

C++, Java

ANSI C, C++

Java

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

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

yes

yes, ANSI Standard SQL 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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

ANSI SQL queries

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JDBC
ODBC

TinkerPop 3

Supported programming languages

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Groovy
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

SQLScript, R

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

Sharding

File partitioning

Customizable business rules for partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication between multi datacenters

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

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

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

when using SQL

yes

Relationships in graphs

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

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

optional

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

yes

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