DBMS > Dragonfly vs. Spark SQL vs. Stardog vs. Yanza

System Properties Comparison Dragonfly vs. Spark SQL vs. Stardog vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Time Series DBMS for IoT Applications

Primary database model

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

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

spark.apache.org/sql

www.stardog.com

yanza.com

Technical documentation

www.dragonflydb.io/docs

spark.apache.org/docs/latest/sql-programming-guide.html

docs.stardog.com

Developer

DragonflyDB team and community contributors

Apache Software Foundation

Stardog-Union

Yanza

Initial release

2023

2014

2010

2015

Current release

1.0, March 2023

3.5.0 ( 2.13), September 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Scala

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
macOS
Windows

Windows

Data scheme

scheme-free

yes

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

HTTP API

Supported programming languages

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

Java
Python
R
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

Lua

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

publish/subscribe channels provide some trigger functionality

yes

via event handlers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Password-based authentication

Access rights for users and roles

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