DBMS > Apache Impala vs. openGauss vs. Realm vs. STSdb vs. Yanza

System Properties Comparison Apache Impala vs. openGauss vs. Realm vs. STSdb vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for Hadoop

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

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

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

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

Website

impala.apache.org

gitee.com/opengauss
opengauss.org

realm.io

github.com/STSSoft/STSdb4

yanza.com

Technical documentation

impala.apache.org/impala-docs.html

docs.opengauss.org/en
gitee.com/opengauss/docs

realm.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Huawei and openGauss community

Realm, acquired by MongoDB in May 2019

STS Soft SC

Yanza

Initial release

2013

2019

2014

2011

2015

Current release

4.1.0, June 2022

3.0, March 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

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

C++

C, C++, Java

Server operating systems

Linux

Android
Backend: server-less
iOS
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

SQL-like DML and DDL statements

ANSI SQL 2011

APIs and other access methods

JDBC
ODBC

.NET Client API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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

yes

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