DBMS > Cassandra vs. IBM Cloudant vs. Manticore Search vs. Spark SQL

System Properties Comparison Cassandra vs. IBM Cloudant vs. Manticore Search vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Database as a Service offering based on Apache CouchDB

Multi-storage database for search, including full-text search.

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Time Series DBMS

using the Manticore Columnar Library

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

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

cassandra.apache.org

www.ibm.com/products/cloudant

manticoresearch.com

spark.apache.org/sql

Technical documentation

cassandra.apache.org/doc/latest

cloud.ibm.com/docs/Cloudant

manual.manticoresearch.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Manticore Software

Apache Software Foundation

Initial release

2008

2010

2017

2014

Current release

4.1.3, July 2023

6.0, February 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

GPL version 2

Open Source

Apache 2.0

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

Erlang

C++

Scala

Server operating systems

BSD
Linux
OS X
Windows

hosted

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

full-text index on all search fields

SQL

Support of SQL

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

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

Proprietary protocol

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

RESTful HTTP/JSON API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Partitioning is done manually, search queries against distributed index is supported

yes, utilizing Spark Core

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

Synchronous replication based on Galera library

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

Eventual 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

atomic operations within a document possible

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users can be defined per object

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...
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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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