DBMS > Cassandra vs. Datastax Enterprise vs. Faircom EDGE vs. FileMaker vs. FoundationDB

System Properties Comparison Cassandra vs. Datastax Enterprise vs. Faircom EDGE vs. FileMaker vs. FoundationDB

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

Ordered key-value store. Core features are complimented by layers.

Primary database model

Wide column store

Key-value store
Relational DBMS

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Secondary database models

Vector DBMS

starting with release V5

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Website

cassandra.apache.org

www.datastax.com/products/datastax-enterprise

www.faircom.com/products/faircom-edge

www.claris.com/filemaker

github.com/apple/foundationdb

Technical documentation

cassandra.apache.org/doc/latest

docs.datastax.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

www.claris.com/resources/documentation

apple.github.io/foundationdb

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

DataStax

FairCom Corporation

Claris

a subsidiary of Apple

FoundationDB

Initial release

2008

2011

1979

1983

2013

Current release

4.1.3, July 2023

6.8, April 2020

V3, October 2020

19.4.1, November 2021

6.2.28, November 2020

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Restricted, free version available

commercial

Open Source

Apache 2.0

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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

ANSI C, C++

C++

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X

Android
Linux

ARM, x86
Raspbian
Windows

iOS

client part only
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

some layers support schemas

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

some layers support typing

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

SQL

Support of SQL

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

SQL-like DML and DDL statements (CQL); Spark SQL

yes

ANSI SQL queries

yes

via plugins

supported in specific SQL layer only

APIs and other access methods

Proprietary protocol

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

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

PHP

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

in SQL-layer only

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

no "single point of failure"

File partitioning

Customizable business rules for partitioning

none

Sharding

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, advanced replication for edge computing

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication, warm standby

since Version 14

yes

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
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency
Tunable Consistency

Linearizable consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

in SQL-layer only

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

Annual subscription
» more

News

Astra Vectorize: Generate Vector Embeddings with 1 Line of Code
22 May 2024

GitHub Copilot + DataStax Astra DB: Build GenAI Apps 100x Faster
21 May 2024

Empowering On-Premises Deployments with Generative AI: Introducing Vector Search for a Self-Managed Modern Architecture
15 May 2024

Tips and Tricks for the DataStax Astra CLI
7 May 2024

How to Build a Crystal Image Search App with Vector Search
25 April 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.