DBMS > Realm vs. Spark SQL vs. STSdb vs. YDB

System Properties Comparison Realm vs. Spark SQL vs. STSdb vs. YDB

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Editorial information provided by DB-Engines

Name

Description

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store

Relational DBMS

Key-value store

Document store
Relational DBMS

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

Score	7.71
Rank	#52	Overall
	#9	Document stores

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Score	0.34
Rank	#285	Overall
	#43	Document stores
	#130	Relational DBMS

Website

realm.io

spark.apache.org/sql

github.com/STSSoft/STSdb4

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

realm.io/docs

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

ydb.tech/en/docs

Developer

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

STS Soft SC

Yandex

Initial release

2014

2011

2019

Current release

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Open Source

Apache 2.0; commercial license available

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

Scala

Server operating systems

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Windows

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

.NET Client API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

Java
Python
R
Scala

C#
Java

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

In-Memory realm

User concepts

Access control

yes

Access rights defined for Yandex Cloud users

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