DBMS > Brytlyt vs. EsgynDB vs. Graphite vs. RDF4J vs. WakandaDB

System Properties Comparison Brytlyt vs. EsgynDB vs. Graphite vs. RDF4J vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

brytlyt.io

www.esgyn.cn

github.com/graphite-project/graphite-web

rdf4j.org

wakanda.github.io

Technical documentation

docs.brytlyt.io

graphite.readthedocs.io

rdf4j.org/documentation

wakanda.github.io/doc

Developer

Brytlyt

Esgyn

Chris Davis

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

Wakanda SAS

Initial release

2016

2015

2006

2004

2012

Current release

5.0, August 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPLv3, extended commercial license available

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++ and CUDA

C++, Java

Python

Java

C++, JavaScript

Server operating systems

Linux
OS X
Windows

Linux

Linux
Unix

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

APIs and other access methods

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

ADO.NET
JDBC
ODBC

HTTP API
Sockets

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

All languages supporting JDBC/ODBC/ADO.Net

JavaScript (Node.js)
Python

Java
PHP
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Java 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

Source-replica replication

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

locking

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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Recent citations in the news

Opensignal Announces Acquisition of Brytlyt GPU-based Data Analytics & Visualization Technology
5 June 2024, PR Web

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
22 December 2021, EU-Startups

Future of Data Visualization and Agile Business Intelligence
17 May 2021, insideHPC

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

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