DBMS > AnzoGraph DB vs. Cassandra vs. FileMaker vs. IBM Db2 Event Store vs. Infobright

System Properties Comparison AnzoGraph DB vs. Cassandra vs. FileMaker vs. IBM Db2 Event Store vs. Infobright

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

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.

Distributed Event Store optimized for Internet of Things use cases

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

Graph DBMS
RDF store

Wide column store

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Website

cambridgesemantics.com/anzograph

cassandra.apache.org

www.claris.com/filemaker

www.ibm.com/products/db2-event-store

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

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

cassandra.apache.org/doc/latest

www.claris.com/resources/documentation

www.ibm.com/docs/en/db2-event-store

Developer

Cambridge Semantics

Apache Software Foundation

Apache top level project, originally developped by Facebook

Claris

a subsidiary of Apple

IBM

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2018

2008

1983

2017

2005

Current release

2.3, January 2021

4.1.3, July 2023

19.4.1, November 2021

2.0

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache version 2

commercial

free developer edition available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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++

Server operating systems

Linux

BSD
Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
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

restricted

only equality queries, not always the best performing solution

yes

Knowledge Grid Technology used instead

SQL

Support of SQL

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

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

yes

via plugins

yes

through the embedded Spark runtime

yes

APIs and other access methods

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

Proprietary protocol

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

Filemaker WebDirect
JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

PHP

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication, warm standby

since Version 14

Active-active shard replication

Source-replica replication

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

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed 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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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