DBMS > Cloudflare Workers KV vs. EsgynDB vs. HBase vs. SQLite vs. Transbase

System Properties Comparison Cloudflare Workers KV vs. EsgynDB vs. HBase vs. SQLite vs. Transbase

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.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Wide-column store based on Apache Hadoop and on concepts of BigTable

Widely used embeddable, in-process RDBMS

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

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

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

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

www.esgyn.cn

hbase.apache.org

www.sqlite.org

www.transaction.de/en/products/transbase.html

Technical documentation

developers.cloudflare.com/kv/api

hbase.apache.org/book.html

www.sqlite.org/docs.html

www.transaction.de/en/products/transbase/features.html

Developer

Cloudflare

Esgyn

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Dwayne Richard Hipp

Transaction Software GmbH

Initial release

2018

2015

2008

2000

1987

Current release

2.3.4, January 2021

3.46.0 (23 May 2024), May 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Public Domain

commercial

free development license

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

Java

C and C++

Server operating systems

hosted

Linux

Linux
Unix
Windows

using Cygwin

server-less

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

schema-free, schema definition possible

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

HTTP REST
Proprietary protocol

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP API
Thrift

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Groovy
Java
PHP
Python
Scala

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
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Coprocessors in Java

yes

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

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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