DBMS > Apache Cassandra vs. ITTIA vs. Warp 10 vs. Yaacomo

System Properties Comparison Apache Cassandra vs. ITTIA vs. Warp 10 vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Edge Time Series DBMS with Real-Time Stream Processing

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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	0.36
Rank	#272	Overall
	#22	Time Series DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

cassandra.apache.org

www.ittia.com

www.warp10.io

yaacomo.com

Technical documentation

cassandra.apache.org/doc/latest

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

ITTIA L.L.C.

SenX

Q2WEB GmbH

Initial release

2008

2007

2015

2009

Current release

5.0-rc1, July 2024

8.7

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache License 2.0

commercial

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 and C++

Java

Server operating systems

BSD
Linux
OS X
Windows

Linux
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

schema-free

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

SQL

Support of SQL

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

yes

APIs and other access methods

Proprietary protocol

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

JDBC
ODBC
RESTful HTTP API
WebSocket

HTTP API
Jupyter
WebSocket

JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

selectable replication factor

based on HBase

Source-replica replication

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

based on HBase

Immediate 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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Database file passwords

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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...
» 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

How to Create Vector Embeddings in Node.js
25 September 2024

Glean and DataStax Partner to Help Developers Harness Powerful Enterprise Search
23 September 2024

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

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.