DBMS > H2 vs. Realm vs. Spark SQL vs. Warp 10

System Properties Comparison H2 vs. Realm vs. Spark SQL vs. Warp 10

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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.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Spatial DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

Technical documentation

www.h2database.com/html/main.html

realm.io/docs

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

www.warp10.io/content/02_Getting_started

Developer

Thomas Mueller

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

SenX

Initial release

2005

2014

2015

Current release

2.2.220, July 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

Open Source

Apache License 2.0

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

Java

Scala

Java

Server operating systems

All OS with a Java VM

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

Java

.Net
Java

with Android only
Objective-C
React Native
Swift

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

runs within the applications so server-side scripts are unnecessary

yes

WarpScript

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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