DBMS > Cloudflare Workers KV vs. Hyprcubd vs. Microsoft SQL Server vs. Trafodion vs. Vitess

System Properties Comparison Cloudflare Workers KV vs. Hyprcubd vs. Microsoft SQL Server vs. Trafodion vs. Vitess

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Serverless Time Series DBMS

Microsofts flagship relational DBMS

Transactional SQL-on-Hadoop DBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

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

hyprcubd.com (offline)

www.microsoft.com/en-us/sql-server

trafodion.apache.org

vitess.io

Technical documentation

developers.cloudflare.com/kv/api

learn.microsoft.com/en-US/sql/sql-server

trafodion.apache.org/documentation.html

vitess.io/docs

Developer

Cloudflare

Hyprcubd, Inc.

Microsoft

Apache Software Foundation, originally developed by HP

The Linux Foundation, PlanetScale

Initial release

2018

1989

2014

2013

Current release

SQL Server 2022, November 2022

2.3.0, February 2019

15.0.2, December 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

Apache Version 2.0, commercial licenses 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++

C++, Java

Server operating systems

hosted

Linux
Windows

Linux

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

HTTP REST
Proprietary protocol

gRPC (https)

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

All languages supporting JDBC/ODBC/ADO.Net

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

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

yes, via HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

token access

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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