DBMS > Cassandra vs. Heroic vs. Ignite vs. SWC-DB

System Properties Comparison Cassandra vs. Heroic vs. Ignite vs. SWC-DB

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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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A high performance, scalable Wide Column DBMS

Primary database model

Wide column store

Time Series DBMS

Key-value store
Relational DBMS

Wide column store

Secondary database models

Vector DBMS

starting with release V5

Time Series DBMS

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

Score	103.86
Rank	#12	Overall
	#1	Wide column stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Website

cassandra.apache.org

github.com/spotify/heroic

ignite.apache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cassandra.apache.org/doc/latest

spotify.github.io/heroic

apacheignite.readme.io/docs

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Spotify

Apache Software Foundation

Alex Kashirin

Initial release

2008

2014

2015

2020

Current release

4.1.3, July 2023

Apache Ignite 2.6

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPL V3

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, .Net

C++

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux

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.

yes

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

via Elasticsearch

yes

SQL

Support of SQL

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

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

APIs and other access methods

Proprietary protocol

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Proprietary protocol
Thrift

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

C++

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

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

yes

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency
Immediate Consistency

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

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

Security Hooks for custom implementations

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.
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Licensing and pricing models

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