DBMS > AlaSQL vs. DolphinDB vs. NCache vs. Newts vs. Stardog

System Properties Comparison AlaSQL vs. DolphinDB vs. NCache vs. Newts vs. Stardog

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Open-Source and Enterprise in-memory Key-Value Store

Time Series DBMS based on Cassandra

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

Primary database model

Document store
Relational DBMS

Secondary database models

Relational DBMS

Document store
Search engine

Using distributed Lucene

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	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

alasql.org

www.dolphindb.com

www.alachisoft.com/ncache

opennms.github.io/newts

www.stardog.com

Technical documentation

github.com/AlaSQL/alasql

docs.dolphindb.cn/en/help200/index.html

www.alachisoft.com/resources/docs

github.com/OpenNMS/newts/wiki

docs.stardog.com

Developer

Andrey Gershun & Mathias R. Wulff

DolphinDB, Inc

Alachisoft

OpenNMS Group

Stardog-Union

Initial release

2014

2018

2005

2014

2010

Current release

v2.00.4, January 2022

5.3, September 2022

7.3.0, May 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

free community version available

Open Source

Enterprise Edition available

Open Source

Apache 2.0

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

C++

C#, .NET, .NET Core, Java

Java

Server operating systems

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

Linux
Windows

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

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 query language

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

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

APIs and other access methods

JavaScript API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

IDistributedCache
JCache
LINQ
Proprietary native 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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Java

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

support for stored procedures with SQL-Server CLR

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Notifications

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

yes, with selectable consistency level

selectable replication factor

based on Cassandra

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

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

yes

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

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

Administrators, Users, Groups

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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