DBMS > AlaSQL vs. Netezza vs. NSDb vs. openGauss vs. STSdb

System Properties Comparison AlaSQL vs. Netezza vs. NSDb vs. openGauss vs. STSdb

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Data warehouse and analytics appliance part of IBM PureSystems

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

alasql.org

www.ibm.com/products/netezza

nsdb.io

gitee.com/opengauss
opengauss.org

github.com/STSSoft/STSdb4

Technical documentation

github.com/AlaSQL/alasql

nsdb.io/Architecture

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

Developer

Andrey Gershun & Mathias R. Wulff

IBM

Huawei and openGauss community

STS Soft SC

Initial release

2014

2000

2017

2019

2011

Current release

3.0, March 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, 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

JavaScript

Java, Scala

C, C++, Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux

included in appliance

Linux
macOS

Linux

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

SQL-like query language

ANSI SQL 2011

APIs and other access methods

JavaScript API

JDBC
ODBC
OLE DB

gRPC
HTTP REST
WebSocket

JDBC
ODBC

.NET Client API

Supported programming languages

JavaScript

C
C++
Fortran
Java
Lua
Perl
Python
R

Java
Scala

C
C++
Java

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by range, list and hash)

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Using Apache Lucene

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept

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

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