DBMS > AlaSQL vs. Bangdb vs. Newts vs. Stardog vs. Valentina Server

System Properties Comparison AlaSQL vs. Bangdb vs. Newts vs. Stardog vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Converged and high performance database for device data, events, time series, document and graph

Time Series DBMS based on Cassandra

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Object-relational database and reports server

Primary database model

Document store
Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

alasql.org

bangdb.com

opennms.github.io/newts

www.stardog.com

www.valentina-db.net

Technical documentation

github.com/AlaSQL/alasql

docs.bangdb.com

github.com/OpenNMS/newts/wiki

docs.stardog.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Andrey Gershun & Mathias R. Wulff

Sachin Sinha, BangDB

OpenNMS Group

Stardog-Union

Paradigma Software

Initial release

2014

2012

2014

2010

1999

Current release

BangDB 2.0, October 2021

7.3.0, May 2020

5.7.5

License

Commercial or Open Source

Open Source

MIT-License

Open Source

BSD 3

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

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

C, C++

Java

Server operating systems

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

Linux

Linux
OS X
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

Import/export of XML data possible

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

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

SQL like support with command line tool

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

JavaScript API

Proprietary protocol
RESTful HTTP API

HTTP REST
Java API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ODBC

Supported programming languages

JavaScript

C
C#
C++
Java
Python

Java

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

yes, Notifications (with Streaming only)

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

based on Cassandra

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable consistency, set CAP knob accordingly

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users and roles

fine grained access rights according to SQL-standard

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