DBMS > BaseX vs. Cassandra vs. Datomic vs. H2 vs. HyperSQL

System Properties Comparison BaseX vs. Cassandra vs. Datomic vs. H2 vs. HyperSQL

Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Native XML DBMS

Wide column store

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Website

Technical documentation

docs.basex.org

cassandra.apache.org/doc/latest

docs.datomic.com

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

Developer

BaseX GmbH

Apache Software Foundation

Apache top level project, originally developped by Facebook

Cognitect

Thomas Mueller

Initial release

2007

2008

2012

2005

2001

Current release

10.7, August 2023

4.1.3, July 2023

1.0.6735, June 2023

2.2.220, July 2023

2.7.2, June 2023

License

Commercial or Open Source

Open Source

BSD license

Open Source

Apache version 2

commercial

limited edition free

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

based on BSD license

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

Java, Clojure

Java

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

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

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Proprietary protocol

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

RESTful HTTP API

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Clojure
Java

Java

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

Java Stored Procedures and User-Defined Functions

Java, SQL

Triggers

yes

via events

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

none

But extensive use of caching in the application peers

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Access rights for users can be defined per object

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...
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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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