DBMS > BigObject vs. Cloudflare Workers KV vs. Kingbase vs. Netezza

System Properties Comparison BigObject vs. Cloudflare Workers KV vs. Kingbase vs. Netezza

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

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	0.13
Rank	#333	Overall
	#147	Relational DBMS

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

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

bigobject.io

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

www.kingbase.com.cn

www.ibm.com/products/netezza

Technical documentation

docs.bigobject.io

developers.cloudflare.com/kv/api

Developer

BigObject, Inc.

Cloudflare

BeiJing KINGBASE Information technologies inc.

IBM

Initial release

2015

2018

1999

2000

Current release

V8.0, August 2021

License

Commercial or Open Source

commercial

free community edition 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 Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux
Windows

Linux

included in appliance

Data scheme

yes

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Standard with numerous extensions

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP REST
Proprietary protocol

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Lua

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Users with fine-grained authorization concept

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