DBMS > Apache Druid vs. HyperSQL vs. RDFox vs. RocksDB

System Properties Comparison Apache Druid vs. HyperSQL vs. RDFox vs. RocksDB

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Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

High performance knowledge graph and semantic reasoning engine

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Graph DBMS
RDF store

Key-value store

Secondary database models

Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

druid.apache.org

hsqldb.org

www.oxfordsemantic.tech

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

hsqldb.org/web/hsqlDocsFrame.html

docs.oxfordsemantic.tech

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Oxford Semantic Technologies

Facebook, Inc.

Initial release

2012

2001

2017

2013

Current release

29.0.1, April 2024

2.7.2, June 2023

6.0, Septermber 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

based on BSD license

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

RDF schemas

schema-free

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

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API
SPARQL 1.1

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC
Java

C
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Roles, resources, and access types

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