DBMS > Blazegraph vs. Dragonfly vs. Oracle vs. Riak TS

System Properties Comparison Blazegraph vs. Dragonfly vs. Oracle vs. Riak TS

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

Widely used RDBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.74
Rank	#217	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

blazegraph.com

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

www.oracle.com/database

Technical documentation

wiki.blazegraph.com

www.dragonflydb.io/docs

docs.oracle.com/en/database

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Blazegraph

DragonflyDB team and community contributors

Oracle

Open Source, formerly Basho Technologies

Initial release

2006

2023

1980

2015

Current release

2.1.5, March 2019

1.0, March 2023

23c, September 2023

3.0.0, September 2022

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

BSL 1.1

commercial

restricted free version is available

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C and C++

Erlang

Server operating systems

Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X

Data scheme

schema-free

scheme-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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

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.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

SPARQL is used as query language

yes

with proprietary extensions

yes, limited

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Lua

PL/SQL

also stored procedures in Java possible

Erlang

Triggers

publish/subscribe channels provide some trigger functionality

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

links between datasets can be stored

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

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

Password-based authentication

fine grained access rights according to SQL-standard

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