DBMS > Bangdb vs. Kinetica vs. Linter vs. Transbase vs. VelocityDB

System Properties Comparison Bangdb vs. Kinetica vs. Linter vs. Transbase vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

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

Fully vectorized database across both GPUs and CPUs

RDBMS for high security requirements

A resource-optimized, high-performance, universally applicable RDBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

Spatial 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	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

bangdb.com

www.kinetica.com

linter.ru

www.transaction.de/en/products/transbase.html

velocitydb.com

Technical documentation

docs.bangdb.com

docs.kinetica.com

www.transaction.de/en/products/transbase/features.html

velocitydb.com/UserGuide

Developer

Sachin Sinha, BangDB

Kinetica

relex.ru

Transaction Software GmbH

VelocityDB Inc

Initial release

2012

1990

1987

2011

Current release

BangDB 2.0, October 2021

7.1, August 2021

Transbase 8.3, 2022

7.x

License

Commercial or Open Source

Open Source

BSD 3

commercial

free development license

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++

C and C++

Server operating systems

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Any that supports .NET

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 DML and DDL statements

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC
Proprietary native API

.Net

Supported programming languages

C
C#
C++
Java
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

.Net

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes, Notifications (with Streaming only)

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Callbacks are triggered when data changes

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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 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

GPU vRAM or System RAM

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Based on Windows Authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News

Share this page