DBMS > Apache Cassandra vs. Drizzle vs. GridDB vs. IBM Cloudant

System Properties Comparison Apache Cassandra vs. Drizzle vs. GridDB vs. IBM Cloudant

Please select another system to include it in the comparison.

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.

Scalable in-memory time series database optimized for IoT and Big Data

Database as a Service offering based on Apache CouchDB

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Key-value store
Relational DBMS

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	2.85
Rank	#95	Overall
	#18	Document stores

Website

cassandra.apache.org

griddb.net

www.ibm.com/products/cloudant

Technical documentation

cassandra.apache.org/doc/latest

docs.griddb.net

cloud.ibm.com/docs/Cloudant

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Drizzle project, originally started by Brian Aker

Toshiba Corporation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2008

2013

2010

Current release

5.0-rc1, July 2024

7.2.4, September 2012

5.1, August 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU GPL

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Cloud-based only

Only available as a cloud service

yes

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++

Erlang

Server operating systems

BSD
Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

Proprietary protocol

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

JDBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP/JSON API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
Java
PHP

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

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

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

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

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 within container, eventual consistency across containers

Eventual Consistency

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

ACID at container level

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

Access rights for users can be defined per database

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...
» 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...
» more

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...
» more

News

DataStax Named a Leader in The Forrester Wave™: Vector Databases, Q3 2024
23 September 2024

How to Build a Notion Clone with Astra DB and Mongoose
20 September 2024

How to Monitor DataStax-Powered RAG Applications with Fiddler
19 September 2024

How Knowledge Graph RAG Boosts LLM Results
18 September 2024

How to Chunk Text in JavaScript for Your RAG Application
18 September 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.