DBMS > Brytlyt vs. Kinetica vs. Lovefield vs. RDF4J vs. SAP HANA

System Properties Comparison Brytlyt vs. Kinetica vs. Lovefield vs. RDF4J vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Fully vectorized database across both GPUs and CPUs

Embeddable relational database for web apps written in pure JavaScript

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

RDF store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

brytlyt.io

www.kinetica.com

google.github.io/lovefield

rdf4j.org

www.sap.com/products/hana.html

Technical documentation

docs.brytlyt.io

docs.kinetica.com

github.com/google/lovefield/blob/master/docs/spec_index.md

rdf4j.org/documentation

help.sap.com/hana

Developer

Brytlyt

Kinetica

Google

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

SAP

Initial release

2016

2012

2014

2004

2010

Current release

5.0, August 2023

7.1, August 2021

2.1.12, February 2017

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++ and CUDA

C, C++

JavaScript

Java

Server operating systems

Linux
OS X
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Unix
Windows

Appliance or cloud-service

Data scheme

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C++
Java
JavaScript (Node.js)
Python

JavaScript

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

yes

SQLScript, R

Triggers

yes

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

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

yes

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