DBMS > DataFS vs. H2 vs. HEAVY.AI vs. Riak TS

System Properties Comparison DataFS vs. H2 vs. HEAVY.AI vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Primary database model

Object oriented DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Graph DBMS

Spatial DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

newdatabase.com

www.h2database.com

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

dev.mobiland.com/Overview.xsp

www.h2database.com/html/main.html

docs.heavy.ai

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

Developer

Mobiland AG

Thomas Mueller

HEAVY.AI, Inc.

Open Source, formerly Basho Technologies

Initial release

2018

2005

2016

2015

Current release

1.1.263, October 2022

2.2.220, July 2023

5.10, January 2022

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2; enterprise edition available

Open Source

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

Java

C++ and CUDA

Erlang

Server operating systems

Windows

All OS with a Java VM

Linux

Linux
OS X

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

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

yes

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C#
C++
VB.Net

Java

All languages supporting JDBC/ODBC/Thrift
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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Erlang

Triggers

no, except callback-events from server when changes happened

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Windows-Profile

fine grained access rights according to SQL-standard

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