DBMS > Apache Cassandra vs. Drizzle vs. HyperSQL vs. Riak TS

System Properties Comparison Apache Cassandra vs. Drizzle vs. HyperSQL vs. Riak TS

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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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Primary database model

Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

cassandra.apache.org

hsqldb.org

Technical documentation

cassandra.apache.org/doc/latest

hsqldb.org/web/hsqlDocsFrame.html

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

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Drizzle project, originally started by Brian Aker

Open Source, formerly Basho Technologies

Initial release

2008

2001

2015

Current release

5.0-rc1, July 2024

7.2.4, September 2012

2.7.2, June 2023

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU GPL

Open Source

based on BSD license

Open Source

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

Erlang

Server operating systems

BSD
Linux
OS X
Windows

FreeBSD
Linux
OS X

All OS with a Java VM

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

Linux
OS X

Data scheme

schema-free

yes

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

restricted

only equality queries, not always the best performing solution

yes

restricted

SQL

Support of SQL

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

yes

with proprietary extensions

yes

yes, limited

APIs and other access methods

Proprietary protocol

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

JDBC

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
Java
PHP

All languages supporting JDBC/ODBC
Java

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

Java, SQL

Erlang

Triggers

yes

hooks for callbacks inside the server can be used.

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Sharding

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

selectable replication factor

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

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

Access rights for users can be defined per object

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

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

Apache 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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