DBMS > Hypertable vs. Kinetica vs. Riak TS vs. Transbase vs. VelocityDB

System Properties Comparison Hypertable vs. Kinetica vs. Riak TS vs. Transbase vs. VelocityDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

Fully vectorized database across both GPUs and CPUs

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Graph DBMS
Object oriented DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

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

Website

www.kinetica.com

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

velocitydb.com

Technical documentation

docs.kinetica.com

www.tiot.jp/riak-docs/riak/ts/latest

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

velocitydb.com/UserGuide

Developer

Hypertable Inc.

Kinetica

Open Source, formerly Basho Technologies

Transaction Software GmbH

VelocityDB Inc

Initial release

2009

2012

2015

1987

2011

Current release

0.9.8.11, March 2016

7.1, August 2021

3.0.0, September 2022

Transbase 8.3, 2022

7.x

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Open Source

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++

Erlang

C and C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Linux
OS X

FreeBSD
Linux
macOS
Solaris
Windows

Any that supports .NET

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

restricted

only exact value or prefix value scans

yes

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes, limited

yes

APIs and other access methods

C++ API
Thrift

JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
Proprietary native API

.Net

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

.Net

Server-side scripts

Stored procedures

user defined functions

Erlang

yes

Triggers

yes

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

yes

pre-commit hooks and post-commit hooks

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Source-replica replication

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Based on Windows Authentication

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