DBMS > Apache Drill vs. Apache IoTDB vs. Cassandra vs. Microsoft Azure Table Storage

System Properties Comparison Apache Drill vs. Apache IoTDB vs. Cassandra vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Document store
Relational DBMS

Time Series DBMS

Wide column store

Secondary database models

Vector DBMS

starting with release V5

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

drill.apache.org

iotdb.apache.org

cassandra.apache.org

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

drill.apache.org/docs

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

cassandra.apache.org/doc/latest

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Microsoft

Initial release

2012

2018

2008

2012

Current release

1.20.3, January 2023

1.1.0, April 2023

4.1.3, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Apache version 2

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

Server operating systems

Linux
OS X
Windows

All OS with a Java VM (>= 1.8)

BSD
Linux
OS X
Windows

hosted

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

yes

restricted

only equality queries, not always the best performing solution

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

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

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
Native API

Proprietary protocol

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

RESTful HTTP API

Supported programming languages

C++

C
C#
C++
Go
Java
Python
Scala

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

no "single point of failure"

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

selectable replication factor

Representation of geographical distribution of servers is possible

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

yes

Access rights for users can be defined per object

Access rights based on private key authentication or shared access signatures

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...
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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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