DBMS > HEAVY.AI vs. Kyligence Enterprise vs. Lovefield vs. Microsoft Azure Table Storage vs. MySQL

System Properties Comparison HEAVY.AI vs. Kyligence Enterprise vs. Lovefield vs. Microsoft Azure Table Storage vs. MySQL

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

A distributed analytics engine for big data, built on top of Apache Kylin

Embeddable relational database for web apps written in pure JavaScript

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used open source RDBMS

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Spatial 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	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

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

kyligence.io/kyligence-enterprise

google.github.io/lovefield

azure.microsoft.com/en-us/services/storage/tables

www.mysql.com

Technical documentation

docs.heavy.ai

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

Developer

HEAVY.AI, Inc.

Kyligence, Inc.

Google

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2014

2012

1995

Current release

5.10, January 2022

2.1.12, February 2017

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++ and CUDA

Java

JavaScript

C and C++

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

optimistic locking

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

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