DBMS > Cloudflare Workers KV vs. IBM Db2 Event Store vs. Neo4j vs. OrientDB

System Properties Comparison Cloudflare Workers KV vs. IBM Db2 Event Store vs. Neo4j vs. OrientDB

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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.

Distributed Event Store optimized for Internet of Things use cases

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Key-value store

Event Store
Time Series DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store

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

Score	0.12
Rank	#305	Overall
	#45	Key-value stores

Score	0.49
Rank	#242	Overall
	#2	Event Stores
	#19	Time Series DBMS

Score	60.14
Rank	#19	Overall
	#1	Graph DBMS

Score	5.14
Rank	#79	Overall
	#14	Document stores
	#5	Graph DBMS
	#12	Key-value stores

Website

www.cloudflare.com/products/workers-kv

www.ibm.com/products/db2-event-store

neo4j.com

orientdb.org

Technical documentation

developers.cloudflare.com/workers/runtime-apis/kv

www.ibm.com/support/knowledgecenter/en/SSGNPV_2.0.0/welcome.html

neo4j.com/docs

www.orientdb.com/docs/last/index.html

Developer

Cloudflare

IBM

Neo4j, Inc.

OrientDB LTD; CallidusCloud; SAP

Initial release

2018

2017

2007

2010

Current release

2.0

4.4.7, May 2022

3.1.9, February 2021

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL version3, commercial licenses available

Open Source

Apache version 2

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C and C++

Java, Scala

Java

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

schema-free and schema-optional

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language, no joins

APIs and other access methods

HTTP REST
Proprietary protocol

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

Java, Javascript

Triggers

yes

via event handler

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes using Neo4j Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationship in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Access rights for users and roles; record level security configurable

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
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