DBMS > Badger vs. EXASOL vs. Kinetica vs. RDF4J vs. Yanza

System Properties Comparison Badger vs. EXASOL vs. Kinetica vs. RDF4J vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Fully vectorized database across both GPUs and CPUs

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

github.com/dgraph-io/badger

www.exasol.com

www.kinetica.com

rdf4j.org

yanza.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.exasol.com/resources

docs.kinetica.com

rdf4j.org/documentation

Developer

DGraph Labs

Exasol

Kinetica

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Yanza

Initial release

2017

2000

2012

2004

2015

Current release

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Unix
Windows

Windows

Data scheme

schema-free

yes

RDF Schemas

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API

Supported programming languages

Java
Lua
Python
R

C++
Java
JavaScript (Node.js)
Python

Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

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

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles on table level

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