DBMS > Bangdb vs. BigchainDB vs. PostGIS vs. Teradata vs. TimesTen

System Properties Comparison Bangdb vs. BigchainDB vs. PostGIS vs. Teradata vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Spatial extension of PostgreSQL

A hybrid cloud data analytics software platform (Teradata Vantage)

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Spatial DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

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

Technical documentation

docs.bangdb.com

bigchaindb.readthedocs.io/en/latest

postgis.net/documentation

docs.teradata.com

docs.oracle.com/database/timesten-18.1

Developer

Sachin Sinha, BangDB

Teradata

Oracle, TimesTen Performance Software, HP

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

Initial release

2012

2016

2005

1984

1998

Current release

BangDB 2.0, October 2021

3.4.2, February 2024

Teradata Vantage 1.0 MU2, January 2019

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

BSD 3

Open Source

AGPL v3

Open Source

GPL v2.0

commercial

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++

Python

Server operating systems

Linux

hosted
Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

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

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL 2016 + extensions

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

CLI Client
RESTful HTTP API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

UDFs, stored procedures, table functions in parallel

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

yes

based on PostgreSQL

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

yes

based on PostgreSQL

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

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,with MongoDB ord RethinkDB

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)

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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