DBMS > Spark SQL vs. STSdb vs. UniData,UniVerse vs. Yanza

System Properties Comparison Spark SQL vs. STSdb vs. UniData,UniVerse 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

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

MultiValue database and application server with SQL mapping layer and meta database capabilities

Time Series DBMS for IoT Applications

Primary database model

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

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

spark.apache.org/sql

github.com/STSSoft/STSdb4

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

yanza.com

Technical documentation

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

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Apache Software Foundation

STS Soft SC

Rocket Software

Yanza

Initial release

2014

2011

1985

2015

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

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

Scala

Server operating systems

Linux
OS X
Windows

Windows

AIX
HP-UX
Linux
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)

optional

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

yes

APIs and other access methods

JDBC
ODBC

.NET Client API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP API

Supported programming languages

Java
Python
R
Scala

C#
Java

.Net
Basic

U2 Basic
C
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

U2 Basic

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

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

configurable

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.

User concepts

Access control

Access rights according to SQL-standard and operating system based

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