DBMS > Cloudflare Workers KV vs. Google Cloud Datastore vs. HyperSQL vs. Microsoft SQL Server vs. TerminusDB

System Properties Comparison Cloudflare Workers KV vs. Google Cloud Datastore vs. HyperSQL vs. Microsoft SQL Server vs. TerminusDB

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.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Microsofts flagship relational DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
RDF store

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

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

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

cloud.google.com/datastore

hsqldb.org

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

terminusdb.com

Technical documentation

developers.cloudflare.com/kv/api

cloud.google.com/datastore/docs

hsqldb.org/web/hsqlDocsFrame.html

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

terminusdb.github.io/terminusdb/#

Developer

Cloudflare

Google

Microsoft

DataChemist Ltd.

Initial release

2018

2008

2001

1989

2018

Current release

2.7.2, June 2023

SQL Server 2022, November 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

restricted free version is available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Prolog, Rust

Server operating systems

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

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 (GQL)

yes

SQL-like query language (WOQL)

APIs and other access methods

HTTP REST
Proprietary protocol

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

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

JavaScript
Python

Server-side scripts

Stored procedures

using Google App Engine

Java, SQL

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

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

none

yes, but depending on the SQL-Server Edition

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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 based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Role-based access control

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