DBMS > AlaSQL vs. jBASE vs. RDF4J vs. Splice Machine

System Properties Comparison AlaSQL vs. jBASE vs. RDF4J vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A robust multi-value DBMS comprising development tools and middleware

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

Document store
Relational DBMS

Multivalue DBMS

RDF store

Relational DBMS

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	1.43
Rank	#160	Overall
	#3	Multivalue DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

alasql.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

rdf4j.org

splicemachine.com

Technical documentation

github.com/AlaSQL/alasql

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

rdf4j.org/documentation

splicemachine.com/how-it-works

Developer

Andrey Gershun & Mathias R. Wulff

Rocket Software (formerly Zumasys)

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

Splice Machine

Initial release

2014

1991

2004

2014

Current release

5.7

3.1, March 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

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

JavaScript

Java

Server operating systems

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

AIX
Linux
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

optional

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

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

JavaScript API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

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

JavaScript

.Net
Basic
Jabbascript
Java

Java
PHP
Python

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

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

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

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Access rights can be defined down to the item level

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

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

Temenos signs first customer in India
24 August 2009, Finextra

provided by Google News

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

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 ...
19 January 2021, PR Newswire

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

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine Hadoop RDBMS Integrated with RedPoint Solution to Deliver Big Data Digital Marketing Platform
7 April 2015, The Fast Mode

provided by Google News

Share this page