DBMS > Cloudflare Workers KV vs. Google BigQuery vs. Google Cloud Spanner vs. IBM Db2 vs. jBASE

System Properties Comparison Cloudflare Workers KV vs. Google BigQuery vs. Google Cloud Spanner vs. IBM Db2 vs. jBASE

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.

Large scale data warehouse service with append-only tables

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Common in IBM host environments, 2 different versions for host and Windows/Linux

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Multivalue DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.39
Rank	#278	Overall
	#39	Key-value stores

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	2.89
Rank	#105	Overall
	#53	Relational DBMS

Score	127.49
Rank	#8	Overall
	#5	Relational DBMS

Score	1.43
Rank	#160	Overall
	#3	Multivalue DBMS

Website

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

cloud.google.com/bigquery

cloud.google.com/spanner

www.ibm.com/products/db2

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

developers.cloudflare.com/kv/api

cloud.google.com/bigquery/docs

cloud.google.com/spanner/docs

www.ibm.com/docs/en/db2

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Cloudflare

Google

IBM

Rocket Software (formerly Zumasys)

Initial release

2018

2010

2017

1983

host version

1991

Current release

12.1, October 2016

5.7

License

Commercial or Open Source

commercial

free version is available

commercial

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 and C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

yes

Query statements complying to ANSI 2011

yes

Embedded SQL for jBASE in BASIC

APIs and other access methods

HTTP REST
Proprietary protocol

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

yes

with separate tools (MQ, InfoSphere)

yes

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

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Strict serializable isolation

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.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.