DBMS > Bangdb vs. BaseX vs. Faircom EDGE vs. Teradata

System Properties Comparison Bangdb vs. BaseX vs. Faircom EDGE vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store
Graph DBMS
Time Series DBMS

Native XML DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series 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	1.73
Rank	#142	Overall
	#4	Native XML DBMS

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

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

bangdb.com

basex.org

www.faircom.com/products/faircom-edge

www.teradata.com

Technical documentation

docs.bangdb.com

docs.basex.org

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

docs.teradata.com

Developer

Sachin Sinha, BangDB

BaseX GmbH

FairCom Corporation

Teradata

Initial release

2012

2007

1979

1984

Current release

BangDB 2.0, October 2021

10.7, August 2023

V3, October 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

BSD 3

Open Source

BSD license

commercial

Restricted, free version available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

ANSI C, C++

Server operating systems

Linux

Linux
OS X
Windows

Android
Linux

ARM, x86
Raspbian
Windows

hosted
Linux

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

XQuery supports types

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL like support with command line tool

yes

ANSI SQL queries

yes

SQL 2016 + extensions

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
Python

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes, Notifications (with Streaming only)

yes

via events

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

File partitioning

Customizable business rules for partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

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
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

multiple readers, single writer

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

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)

Users with fine-grained authorization concept on 4 levels

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

fine grained access rights according to SQL-standard

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More resources

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