DBMS > Apache Cassandra vs. BaseX vs. Coveo vs. HEAVY.AI

System Properties Comparison Apache Cassandra vs. BaseX vs. Coveo vs. HEAVY.AI

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	2.14
Rank	#116	Overall
	#11	Search engines

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Website

cassandra.apache.org

basex.org

www.coveo.com

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

cassandra.apache.org/doc/latest

docs.basex.org

docs.coveo.com

docs.heavy.ai

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

BaseX GmbH

Coveo

HEAVY.AI, Inc.

Initial release

2008

2007

2012

2016

Current release

5.0-rc1, July 2024

11.2, August 2024

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

BSD license

commercial

Open Source

Apache Version 2; enterprise edition available

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++ and CUDA

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

hosted

Linux

Data scheme

schema-free

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

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

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C#
Java
JavaScript
Python

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

yes

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

none

yes

Multi-source 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

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

multiple readers, single writer

yes

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

Users with fine-grained authorization concept on 4 levels

granular access controls, API key management, content filters

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

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

How Knowledge Graph RAG Boosts LLM Results
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.