DBMS > Blazegraph vs. Cloudflare Workers KV vs. Dragonfly vs. OrigoDB vs. SAP HANA

System Properties Comparison Blazegraph vs. Cloudflare Workers KV vs. Dragonfly vs. OrigoDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

A fully ACID in-memory object graph database

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Graph DBMS
RDF store

Key-value store

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

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

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

blazegraph.com

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

github.com/dragonflydb/dragonfly
www.dragonflydb.io

origodb.com

www.sap.com/products/hana.html

Technical documentation

wiki.blazegraph.com

developers.cloudflare.com/kv/api

www.dragonflydb.io/docs

origodb.com/docs

help.sap.com/hana

Developer

Blazegraph

Cloudflare

DragonflyDB team and community contributors

Robert Friberg et al

SAP

Initial release

2006

2018

2023

2009

under the name LiveDB

2010

Current release

2.1.5, March 2019

1.0, March 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

Open Source

BSL 1.1

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

Linux
Windows

Appliance or cloud-service

Data scheme

schema-free

scheme-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

strings, hashes, lists, sets, sorted sets, bit arrays

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP REST
Proprietary protocol

Proprietary protocol

RESP - REdis Serialization Protocol

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net

Server-side scripts

Stored procedures

yes

Lua

yes

SQLScript, R

Triggers

publish/subscribe channels provide some trigger functionality

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

depending on model

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

Password-based authentication

Role based authorization

yes

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