DBMS > Cassandra vs. Faircom EDGE vs. Google Cloud Bigtable vs. Newts

System Properties Comparison Cassandra vs. Faircom EDGE vs. Google Cloud Bigtable vs. Newts

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Time Series DBMS based on Cassandra

Primary database model

Wide column store

Key-value store
Relational DBMS

Key-value store
Wide column store

Time Series DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

cassandra.apache.org

www.faircom.com/products/faircom-edge

cloud.google.com/bigtable

opennms.github.io/newts

Technical documentation

cassandra.apache.org/doc/latest

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

cloud.google.com/bigtable/docs

github.com/OpenNMS/newts/wiki

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

FairCom Corporation

Google

OpenNMS Group

Initial release

2008

1979

2015

2014

Current release

4.1.3, July 2023

V3, October 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

yes

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

ANSI C, C++

Java

Server operating systems

BSD
Linux
OS X
Windows

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL 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.

yes

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)

yes

ANSI SQL queries

APIs and other access methods

Proprietary protocol

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

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

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP REST
Java API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

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

Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

File partitioning

Customizable business rules for partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

Synchronous and asynchronous realtime replication based on transaction logs

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor

based on Cassandra

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

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Atomic single-row operations

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.

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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.
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Licensing and pricing models

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