DBMS > Cassandra vs. Drizzle vs. RDF4J vs. RisingWave

System Properties Comparison Cassandra vs. Drizzle vs. RDF4J vs. RisingWave

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Website

cassandra.apache.org

rdf4j.org

www.risingwave.com/database

Technical documentation

cassandra.apache.org/doc/latest

rdf4j.org/documentation

docs.risingwave.com/docs/current/intro

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Drizzle project, originally started by Brian Aker

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

RisingWave Labs

Initial release

2008

2004

2022

Current release

4.1.3, July 2023

7.2.4, September 2012

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU GPL

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

Java

Rust

Server operating systems

BSD
Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

with proprietary extensions

yes

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
PostgreSQL wire protocol

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
Java
PHP

Java
PHP
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

UDFs in Python or Java

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Isolation support depends on the API used

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

Access rights for users can be defined per object

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users and Roles

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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