DBMS > AlaSQL vs. BigObject vs. Newts vs. OpenQM vs. Stardog

System Properties Comparison AlaSQL vs. BigObject vs. Newts vs. OpenQM vs. Stardog

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Analytic DBMS for real-time computations and queries

Time Series DBMS based on Cassandra

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Primary database model

Document store
Relational DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Multivalue DBMS

Graph DBMS
RDF store

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

alasql.org

bigobject.io

opennms.github.io/newts

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

www.stardog.com

Technical documentation

github.com/AlaSQL/alasql

docs.bigobject.io

github.com/OpenNMS/newts/wiki

docs.stardog.com

Developer

Andrey Gershun & Mathias R. Wulff

BigObject, Inc.

OpenNMS Group

Rocket Software, originally Martin Phillips

Stardog-Union

Initial release

2014

2015

2014

1993

2010

Current release

3.4-12

7.3.0, May 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

free community edition available

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

commercial

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

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)

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

yes

with some exceptions

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

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

SQL-like DML and DDL statements

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

APIs and other access methods

JavaScript API

fluentd
ODBC
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

Supported programming languages

JavaScript

Java

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

yes

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

relationships in graphs

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

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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 and roles

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