DBMS > Apache Cassandra vs. Graph Engine

System Properties Comparison Apache Cassandra vs. Graph Engine

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Our visitors often compare Apache Cassandra and Graph Engine with Neo4j, Google Cloud Spanner and GraphDB.

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Primary database model

Wide column store

Graph DBMS
Key-value store

Secondary database models

Vector DBMS

starting with release V5

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

Score	108.05
Rank	#11	Overall
	#1	Wide column stores

Score	0.58
Rank	#239	Overall
	#21	Graph DBMS
	#34	Key-value stores

Website

cassandra.apache.org

www.graphengine.io

Technical documentation

cassandra.apache.org/doc/latest

www.graphengine.io/docs/manual

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Microsoft

Initial release

2008

2010

Current release

5.0-rc1, July 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

.NET and C

Server operating systems

BSD
Linux
OS X
Windows

.NET

Data scheme

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.

Secondary indexes

restricted

only equality queries, not always the best performing solution

SQL

Support of SQL

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

APIs and other access methods

Proprietary protocol

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

RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

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

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

More information provided by the system vendor

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