DBMS > Bangdb vs. Microsoft Azure Table Storage vs. TerminusDB vs. TimesTen

System Properties Comparison Bangdb vs. Microsoft Azure Table Storage vs. TerminusDB vs. TimesTen

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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

A Wide Column Store for rapid development using massive semi-structured datasets

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Wide column store

Graph DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

bangdb.com

azure.microsoft.com/en-us/services/storage/tables

terminusdb.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.bangdb.com

terminusdb.github.io/terminusdb/#

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Sachin Sinha, BangDB

Microsoft

DataChemist Ltd.

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2018

1998

Current release

BangDB 2.0, October 2021

11.0.0, January 2023

Release 22.1

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Prolog, Rust

Server operating systems

Linux

hosted

Linux

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

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

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language (WOQL)

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C
C#
C++
Java
Python

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

JavaScript
Python

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

PL/SQL

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

Implicit feature of the cloud service

Graph Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Journaling Streams

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

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

in-memory journaling

yes

by means of logfiles and checkpoints

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)

Access rights based on private key authentication or shared access signatures

Role-based access control

fine grained access rights according to SQL-standard

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