DBMS > Heroic vs. LevelDB vs. RDFox vs. Transbase

System Properties Comparison Heroic vs. LevelDB vs. RDFox vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

High performance knowledge graph and semantic reasoning engine

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

github.com/spotify/heroic

github.com/google/leveldb

www.oxfordsemantic.tech

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

Technical documentation

spotify.github.io/heroic

github.com/google/leveldb/blob/main/doc/index.md

docs.oxfordsemantic.tech

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

Developer

Spotify

Google

Oxford Semantic Technologies

Transaction Software GmbH

Initial release

2014

2011

2017

1987

Current release

1.23, February 2021

6.0, Septermber 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

commercial

free development license

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++

C and C++

Server operating systems

Illumos
Linux
OS X
Windows

Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

RDF schemas

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

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP API
SPARQL 1.1

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
Java

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

replication via a shared file system

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Roles, resources, and access types

fine grained access rights according to SQL-standard

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