DBMS > Cloudflare Workers KV vs. GeoMesa vs. Lovefield vs. Splice Machine

System Properties Comparison Cloudflare Workers KV vs. GeoMesa vs. Lovefield vs. Splice Machine

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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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Embeddable relational database for web apps written in pure JavaScript

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Key-value store

Spatial DBMS

Relational DBMS

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

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

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

www.geomesa.org

google.github.io/lovefield

splicemachine.com

Technical documentation

developers.cloudflare.com/kv/api

www.geomesa.org/documentation/stable/user/index.html

github.com/google/lovefield/blob/master/docs/spec_index.md

splicemachine.com/how-it-works

Developer

Cloudflare

CCRi and others

Google

Splice Machine

Initial release

2018

2014

Current release

4.0.5, February 2024

2.1.12, February 2017

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

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

Scala

JavaScript

Java

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Solaris
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

HTTP REST
Proprietary protocol

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

JavaScript

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

depending on storage layer

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

yes

using MemoryDB

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users, groups and roles according to SQL-standard

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Related products and services

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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