DBMS > Cloudflare Workers KV vs. Hive vs. mSQL vs. Pinecone vs. SQLite

System Properties Comparison Cloudflare Workers KV vs. Hive vs. mSQL vs. Pinecone vs. SQLite

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

mSQL (Mini SQL) is a simple and lightweight RDBMS

A managed, cloud-native vector database

Widely used embeddable, in-process RDBMS

Primary database model

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

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

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

hive.apache.org

hughestech.com.au/products/msql

www.pinecone.io

www.sqlite.org

Technical documentation

developers.cloudflare.com/kv/api

cwiki.apache.org/confluence/display/Hive/Home

docs.pinecone.io/docs/overview

www.sqlite.org/docs.html

Developer

Cloudflare

Apache Software Foundation

initially developed by Facebook

Hughes Technologies

Pinecone Systems, Inc

Dwayne Richard Hipp

Initial release

2018

2012

1994

2019

2000

Current release

3.1.3, April 2022

4.4, October 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

free licenses can be provided

commercial

Open Source

Public Domain

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

Java

Server operating systems

hosted

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

hosted

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP REST
Proprietary protocol

JDBC
ODBC
Thrift

JDBC
ODBC

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C++
Java
PHP
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

Python

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

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

via file-system locks

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

Access rights for users, groups and roles

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.