DBMS > Apache Druid vs. RDF4J vs. RisingWave vs. Sequoiadb

System Properties Comparison Apache Druid vs. RDF4J vs. RisingWave vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS
Time Series DBMS

RDF store

Relational DBMS

Document store
Relational DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

druid.apache.org

rdf4j.org

www.risingwave.com/database

www.sequoiadb.com

Technical documentation

druid.apache.org/docs/latest/design

rdf4j.org/documentation

docs.risingwave.com/docs/current/intro

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Apache Software Foundation and contributors

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

RisingWave Labs

Sequoiadb Ltd.

Initial release

2012

2004

2022

2013

Current release

29.0.1, April 2024

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Rust

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Linux

Data scheme

yes

schema-less columns are supported

yes

RDF Schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
PostgreSQL wire protocol

proprietary protocol using JSON

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java
PHP
Python

Go
Java
JavaScript (Node.js)
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

UDFs in Python or Java

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Users and Roles

simple password-based access control

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