DBMS > Cloudflare Workers KV vs. Postgres-XL vs. StarRocks vs. Trafodion

System Properties Comparison Cloudflare Workers KV vs. Postgres-XL vs. StarRocks vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

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

www.postgres-xl.org

www.starrocks.io

trafodion.apache.org

Technical documentation

developers.cloudflare.com/kv/api

www.postgres-xl.org/documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

trafodion.apache.org/documentation.html

Developer

Cloudflare

The Linux Foundation

since Feb 2023

Apache Software Foundation, originally developed by HP

Initial release

2018

2014

since 2012, originally named StormDB

2020

2014

Current release

10 R1, October 2018

2.5.3, March 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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++, Java

Server operating systems

hosted

Linux
macOS

Linux

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

HTTP REST
Proprietary protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
MySQL protocol

ADO.NET
JDBC
ODBC

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning (by range and hash)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HBase

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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