DBMS > Cloudflare Workers KV vs. GreptimeDB vs. mSQL vs. Quasardb vs. SQLite

System Properties Comparison Cloudflare Workers KV vs. GreptimeDB vs. mSQL vs. Quasardb 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.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

mSQL (Mini SQL) is a simple and lightweight RDBMS

Distributed, high-performance timeseries 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	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

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

greptime.com

hughestech.com.au/products/msql

quasar.ai

www.sqlite.org

Technical documentation

developers.cloudflare.com/kv/api

docs.greptime.com

doc.quasar.ai/master

www.sqlite.org/docs.html

Developer

Cloudflare

Greptime Inc.

Hughes Technologies

quasardb

Dwayne Richard Hipp

Initial release

2018

2022

1994

2009

2000

Current release

4.4, October 2021

3.14.1, January 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free licenses can be provided

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Rust

C++

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

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

BSD
Linux
OS X
Windows

server-less

Data scheme

schema-free

schema-free, schema definition possible

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

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

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP REST
Proprietary protocol

gRPC
HTTP API
JDBC

JDBC
ODBC

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C++
Erlang
Go
Java
JavaScript

C
C++
Delphi
Java
Perl
PHP
Tcl

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

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

Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

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

via file-system locks

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Simple rights management via user accounts

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.