DBMS > Cachelot.io vs. HEAVY.AI vs. Lovefield vs. MySQL vs. Realm

System Properties Comparison Cachelot.io vs. HEAVY.AI vs. Lovefield vs. MySQL vs. Realm

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

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

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Document store

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

cachelot.io

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

google.github.io/lovefield

www.mysql.com

realm.io

Technical documentation

docs.heavy.ai

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

dev.mysql.com/doc

realm.io/docs

Developer

HEAVY.AI, Inc.

Google

Oracle

since 2010, originally MySQL AB, then Sun

Realm, acquired by MongoDB in May 2019

Initial release

2015

2016

2014

1995

2014

Current release

5.10, January 2022

2.1.12, February 2017

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++

C++ and CUDA

JavaScript

C and C++

Server operating systems

FreeBSD
Linux
OS X

Linux

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

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

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

Memcached protocol

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

proprietary syntax

runs within the applications so server-side scripts are unnecessary

Triggers

Using read-only observers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

not for MyISAM storage engine

ACID

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

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.