DBMS > HEAVY.AI vs. Microsoft Azure AI Search vs. openGauss vs. OrigoDB

System Properties Comparison HEAVY.AI vs. Microsoft Azure AI Search vs. openGauss vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Search-as-a-service for web and mobile app development

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

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Search engine

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Spatial DBMS

Vector DBMS

Document store
Spatial DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/en-us/services/search

gitee.com/opengauss
opengauss.org

origodb.com

Technical documentation

docs.heavy.ai

learn.microsoft.com/en-us/azure/search

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

origodb.com/docs

Developer

HEAVY.AI, Inc.

Microsoft

Huawei and openGauss community

Robert Friberg et al

Initial release

2016

2015

2019

2009

under the name LiveDB

Current release

5.10, January 2022

3.0, March 2022

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++ and CUDA

C, C++, Java

Server operating systems

Linux

hosted

Linux

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL 2011

APIs and other access methods

JDBC
ODBC
Thrift
Vega

RESTful HTTP API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java
JavaScript
Python

C
C++
Java

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Implicit feature of the cloud service

horizontal partitioning (by range, list and hash)

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

Source-replica 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

yes

depending on model

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

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using Azure authentication

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

Role based authorization

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More resources

Recent citations in the news

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19 March 2024, Datanami

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openGauss Open Source Community Officially Launch
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