DBMS > Cloudflare Workers KV vs. HEAVY.AI vs. Lovefield vs. SQLite vs. YottaDB

System Properties Comparison Cloudflare Workers KV vs. HEAVY.AI vs. Lovefield vs. SQLite vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

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 embeddable, in-process RDBMS

A fast and solid embedded Key-value store

Primary database model

Key-value store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

www.cloudflare.com/developer-platform/workers-kv

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

google.github.io/lovefield

www.sqlite.org

yottadb.com

Technical documentation

developers.cloudflare.com/kv/api

docs.heavy.ai

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

www.sqlite.org/docs.html

yottadb.com/resources/documentation

Developer

Cloudflare

HEAVY.AI, Inc.

Google

Dwayne Richard Hipp

YottaDB, LLC

Initial release

2018

2016

2014

2000

2001

Current release

5.10, January 2022

2.1.12, February 2017

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

AGPL 3.0

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

JavaScript

Server operating systems

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

server-less

Docker
Linux

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

by using the Octo plugin

APIs and other access methods

HTTP REST
Proprietary protocol

JDBC
ODBC
Thrift
Vega

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Users and groups based on OS-security mechanisms

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