DBMS > AllegroGraph vs. Badger vs. ClickHouse vs. Cloudflare Workers KV vs. Datomic

System Properties Comparison AllegroGraph vs. Badger vs. ClickHouse vs. Cloudflare Workers KV vs. Datomic

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Website

allegrograph.com

github.com/dgraph-io/badger

clickhouse.com

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

www.datomic.com

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

godoc.org/github.com/dgraph-io/badger

clickhouse.com/docs

developers.cloudflare.com/kv/api

docs.datomic.com

Developer

Franz Inc.

DGraph Labs

Clickhouse Inc.

Cloudflare

Cognitect

Initial release

2004

2017

2016

2018

2012

Current release

8.0, December 2023

v24.4.1.2088-stable, May 2024

1.0.7075, December 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

limited edition free

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java, Clojure

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS

hosted

All OS with a Java VM

Data scheme

yes

RDF schemas

schema-free

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.

bulk load of XML files possible

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

RESTful HTTP API
SPARQL

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

HTTP REST
Proprietary protocol

RESTful HTTP API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Clojure
Java

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Transaction Functions

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

key based and custom

none

But extensive use of caching in the application peers

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

none

But extensive use of caching in the application peers

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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News

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23 May 2024

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9 February 2024

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23 January 2024

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