DBMS > Brytlyt vs. Citus vs. RDF4J vs. Splice Machine

System Properties Comparison Brytlyt vs. Citus vs. RDF4J vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

RDF store

Relational DBMS

Secondary database models

Document store

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

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

Technical documentation

docs.brytlyt.io

docs.citusdata.com

rdf4j.org/documentation

splicemachine.com/how-it-works

Developer

Brytlyt

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

Splice Machine

Initial release

2016

2010

2004

2014

Current release

5.0, August 2023

8.1, December 2018

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPL 3.0, 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

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

APIs and other access methods

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
PHP
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

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

Brytlyt Unleashes Serverless GPU-Acceleration for Analytics
15 September 2021, PR Newswire

provided by Google News

Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL performance and scale
24 January 2019, blogs.microsoft.com

Ubicloud wants to build an open source alternative to AWS
5 March 2024, TechCrunch

Microsoft acquires Citus Data, creators of a cloud-friendly version of the PostgreSQL database
24 January 2019, GeekWire

Microsoft buys an open source database startup to give it an edge against Amazon Web Services
24 January 2019, Business Insider

Microsoft acquires another open-source company, Citus Data
24 January 2019, CNBC

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning
19 January 2021, PR Newswire

Monte Zweben's Splice Machine Introduces New Hadoop RDBMS
24 June 2014, Forbes

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Hadoop is not a static data repository, says Splice Machine CEO | #BigDataSV
12 February 2014, SiliconANGLE News

provided by Google News

Share this page