DBMS > Bangdb vs. Kinetica vs. Teradata Aster

System Properties Comparison Bangdb vs. Kinetica vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Fully vectorized database across both GPUs and CPUs

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial 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	0.66
Rank	#234	Overall
	#107	Relational DBMS

Website

bangdb.com

www.kinetica.com

Technical documentation

docs.bangdb.com

docs.kinetica.com

Developer

Sachin Sinha, BangDB

Kinetica

Teradata

Initial release

2012

2005

Current release

BangDB 2.0, October 2021

7.1, August 2021

License

Commercial or Open Source

Open Source

BSD 3

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++

Server operating systems

Linux

Data scheme

schema-free

yes

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

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
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

R packages

Triggers

yes, Notifications (with Streaming only)

yes

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

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

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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

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

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

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More resources

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