DBMS > HEAVY.AI vs. Microsoft Azure SQL Database vs. OpenTenBase vs. Spark SQL

System Properties Comparison HEAVY.AI vs. Microsoft Azure SQL Database vs. OpenTenBase vs. Spark SQL

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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

Database as a Service offering with high compatibility to Microsoft SQL Server

An enterprise-level distributed HTAP open source database based on PostgreSQL

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.08
Rank	#370	Overall
	#156	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

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

azure.microsoft.com/en-us/products/azure-sql/database

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

spark.apache.org/sql

Technical documentation

docs.heavy.ai

docs.microsoft.com/en-us/azure/azure-sql

docs.opentenbase.org
docs.opentenbase.org/en

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

Developer

HEAVY.AI, Inc.

Microsoft

OpenAtom Foundation, previously Tencent

Apache Software Foundation

Initial release

2016

2010

2014

Current release

5.10, January 2022

V12

2.5, January 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

BSD-3

Open Source

Apache 2.0

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++

Scala

Server operating systems

Linux

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
Go
Java
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, with always 3 replicas available

yes

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

show all

Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

Making the most of geospatial intelligence
14 April 2023, InfoWorld

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

provided by Google News

Copilot in Azure SQL Database in Private Preview
27 March 2024, InfoQ.com

Microsoft unveils Copilot for Azure SQL Database
27 March 2024, InfoWorld

Public Preview: New Azure SQL Database skills introduced to Microsoft Copilot in Azure | Azure updates
21 May 2024, Microsoft

Azure SQL Database migration to OCI - resources estimation and migration approach
11 January 2024, Oracle

Expand the limits of innovation with Azure data
21 March 2024, Microsoft

provided by Google News

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

provided by Google News

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