DBMS > chDB vs. Cloudflare Workers KV vs. GeoSpock vs. Greenplum vs. H2GIS

System Properties Comparison chDB vs. Cloudflare Workers KV vs. GeoSpock vs. Greenplum vs. H2GIS

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

An embedded SQL OLAP Engine powered by ClickHouse

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

Spatial and temporal data processing engine for extreme data scale

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Spatial extension of H2

Primary database model

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	0.07
Rank	#376	Overall
	#158	Relational DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Website

github.com/chdb-io/chdb

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

geospock.com

greenplum.org

www.h2gis.org

Technical documentation

doc.chdb.io

developers.cloudflare.com/kv/api

docs.greenplum.org

www.h2gis.org/docs/home

Developer

Cloudflare

GeoSpock

Pivotal Software Inc.

CNRS

Initial release

2023

2018

2005

2013

Current release

2.0, September 2019

7.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

LGPL 3.0

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

Java, Javascript

Java

Server operating systems

server-less

hosted

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

since Version 4.2

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

HTTP REST
Proprietary protocol

JDBC

JDBC
ODBC

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C
Java
Perl
Python
R

Java

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

based on H2

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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 rights for users can be defined per table

fine grained access rights according to SQL-standard

yes

based on H2

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