DBMS > AnzoGraph DB vs. ArcadeDB vs. Cassandra vs. FileMaker

System Properties Comparison AnzoGraph DB vs. ArcadeDB vs. Cassandra vs. FileMaker

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Wide column store

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Website

cambridgesemantics.com/anzograph

arcadedb.com

cassandra.apache.org

www.claris.com/filemaker

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.arcadedb.com

cassandra.apache.org/doc/latest

www.claris.com/resources/documentation

Developer

Cambridge Semantics

Arcade Data

Apache Software Foundation

Apache top level project, originally developped by Facebook

Claris

a subsidiary of Apple

Initial release

2018

2021

2008

1983

Current release

2.3, January 2021

September 2021

4.1.3, July 2023

19.4.1, November 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

Apache version 2

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

Server operating systems

Linux

All OS with a Java VM

BSD
Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

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

A http query request can return the data in XML format

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language, no joins

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

yes

via plugins

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

Proprietary protocol

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

Filemaker WebDirect
JDBC
ODBC

Supported programming languages

C++
Java
Python

Java

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

PHP

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication, warm standby

since Version 14

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

not needed in graphs

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

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 and roles

Access rights for users can be defined per object

simple rights management via user accounts and connection to external directory services

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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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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