DBMS > Cassandra vs. IRONdb vs. Microsoft Access vs. Milvus vs. RDF4J

System Properties Comparison Cassandra vs. IRONdb vs. Microsoft Access vs. Milvus vs. RDF4J

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

A DBMS designed for efficient storage of vector data and vector similarity searches

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

cassandra.apache.org

www.circonus.com/solutions/time-series-database/

www.microsoft.com/en-us/microsoft-365/access

milvus.io

rdf4j.org

Technical documentation

cassandra.apache.org/doc/latest

docs.circonus.com/irondb/category/getting-started

developer.microsoft.com/en-us/access

milvus.io/docs/overview.md

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Circonus LLC.

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2008

2017

1992

2019

2004

Current release

4.1.3, July 2023

V0.10.20, January 2018

1902 (16.0.11328.20222), March 2019

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Bundled with Microsoft Office

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C and C++

C++

C++, Go

Java

Server operating systems

BSD
Linux
OS X
Windows

Linux

Windows

Not a real database server, but making use of DLLs

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

Vector, Numeric and String

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)

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

but not compliant to any SQL standard

APIs and other access methods

Proprietary protocol

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

HTTP API

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C++
Go
Java
JavaScript (Node.js)
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

yes

since Access 2010 using the ACE-engine

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Automatic, metric affinity per node

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

configurable replication factor, datacenter aware

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 per node, eventual consistency across nodes

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable 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

ACID

but no files for transaction logging

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

in-memory storage is supported as well

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

a simple user-level security was built in till version Access 2003

Role based access control and fine grained access rights

More information provided by the system vendor

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