DBMS > Realm vs. Splice Machine vs. STSdb vs. Yanza

System Properties Comparison Realm vs. Splice Machine vs. STSdb vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Time Series DBMS for IoT Applications

Primary database model

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

Score	7.71
Rank	#52	Overall
	#9	Document stores

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

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

Website

realm.io

splicemachine.com

github.com/STSSoft/STSdb4

yanza.com

Technical documentation

realm.io/docs

splicemachine.com/how-it-works

Developer

Realm, acquired by MongoDB in May 2019

Splice Machine

STS Soft SC

Yanza

Initial release

2014

2011

2015

Current release

3.1, March 2021

4.0.8, September 2015

License

Commercial or Open Source

Open Source

AGPL 3.0, commercial license available

Open Source

GPLv2, commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Android
Backend: server-less
iOS
Windows

Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

APIs and other access methods

JDBC
Native Spark Datasource
ODBC

.NET Client API

HTTP API

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C#
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes

Java

Triggers

yes

Change Listeners

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

yes

Access rights for users, groups and roles according to SQL-standard

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More resources

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