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

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

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

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

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	3.04
Rank	#85	Overall
	#46	Relational DBMS

Score	21.62
Rank	#29	Overall
	#18	Relational DBMS

Score	0.85
Rank	#203	Overall
	#30	Key-value stores

Website

db.apache.org/derby

spark.apache.org/sql

www.alachisoft.com/ncache

Technical documentation

db.apache.org/derby/manuals/index.html

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

www.alachisoft.com/resources/docs

Developer

Apache Software Foundation

Alachisoft

Initial release

1997

2014

2005

Current release

10.17.1.0, November 2023

3.5.0 ( 2.13), September 2023

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Enterprise Edition available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

C#, .NET, .NET Core, Java

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

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

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

yes

SQL-like DML and DDL statements

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

APIs and other access methods

JDBC

JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

Java

Java
Python
R
Scala

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

Server-side scripts

Stored procedures

Java Stored Procedures

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

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

fine grained access rights according to SQL-standard

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

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