DBMS > Cloudflare Workers KV vs. Datomic vs. Ingres vs. KeyDB vs. RocksDB

System Properties Comparison Cloudflare Workers KV vs. Datomic vs. Ingres vs. KeyDB vs. RocksDB

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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Well established RDBMS

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store

Relational DBMS

Key-value store

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

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

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

www.datomic.com

www.actian.com/databases/ingres

github.com/Snapchat/KeyDB
keydb.dev

rocksdb.org

Technical documentation

developers.cloudflare.com/kv/api

docs.datomic.com

docs.actian.com/ingres

docs.keydb.dev

github.com/facebook/rocksdb/wiki

Developer

Cloudflare

Cognitect

Actian Corporation

EQ Alpha Technology Ltd.

Facebook, Inc.

Initial release

2018

2012

1974

originally developed at University Berkely in early 1970s

2019

2013

Current release

1.0.7075, December 2023

11.2, May 2022

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

BSD-3

Open Source

BSD

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, Clojure

C++

Server operating systems

hosted

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

by using the Redis Search module

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST
Proprietary protocol

RESTful HTTP API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Proprietary protocol

RESP - REdis Serialization Protoco

C++ API
Java API

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Clojure
Java

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Lua

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Ingres Replicator

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control and ACL

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