DBMS > Apache Spark (SQL) vs. NCache vs. Stardog

System Properties Comparison Apache Spark (SQL) vs. NCache vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

Apache Spark SQL is a component on top of 'Spark Core' for structured data processing

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

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

Primary database model

Relational DBMS

Key-value store

Graph DBMS
RDF store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	20.40
Rank	#29	Overall
	#18	Relational DBMS

Score	0.84
Rank	#201	Overall
	#30	Key-value stores

Score	1.58
Rank	#137	Overall
	#12	Graph DBMS
	#6	RDF stores

Website

spark.apache.org/sql

www.alachisoft.com/ncache

www.stardog.com

Technical documentation

spark.apache.org/docs/latest/sql-programming-guide.html

www.alachisoft.com/resources/docs

docs.stardog.com

Developer

Apache Software Foundation

Alachisoft

Stardog-Union

Initial release

2014

2005

2010

Current release

3.5.0 ( 2.13), September 2023

5.3.3, April 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Enterprise Edition 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

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Implementation language

Scala

C#, .NET, .NET Core, Java

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
macOS
Windows

Data scheme

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

SQL-like DML and DDL statements

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

JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native 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

Java
Python
R
Scala

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

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

yes, utilizing Spark Core

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

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

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

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

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

Access rights for users and roles

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