DBMS > Cassandra vs. Google Cloud Datastore vs. Microsoft Access vs. Neo4j vs. Oracle Coherence

System Properties Comparison Cassandra vs. Google Cloud Datastore vs. Microsoft Access vs. Neo4j vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Oracles in-memory data grid solution

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

cassandra.apache.org

cloud.google.com/datastore

www.microsoft.com/en-us/microsoft-365/access

neo4j.com

www.oracle.com/java/coherence

Technical documentation

cassandra.apache.org/doc/latest

cloud.google.com/datastore/docs

developer.microsoft.com/en-us/access

neo4j.com/docs

docs.oracle.com/en/middleware/standalone/coherence

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

Microsoft

Neo4j, Inc.

Oracle

Initial release

2008

1992

2007

Current release

4.1.3, July 2023

1902 (16.0.11328.20222), March 2019

5.20, May 2024

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Bundled with Microsoft Office

Open Source

GPL version3, commercial licenses available

commercial

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java

C++

Java, Scala

Java

Server operating systems

BSD
Linux
OS X
Windows

hosted

Windows

Not a real database server, but making use of DLLs

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

All OS with a Java VM

Data scheme

schema-free

yes

schema-free and schema-optional

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

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

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

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

SQL-like query language (GQL)

yes

but not compliant to any SQL standard

APIs and other access methods

Proprietary protocol

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

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

JCache
JPA
RESTful HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

.Net
C++
Java

Server-side scripts

Stored procedures

using Google App Engine

yes

since Access 2010 using the ACE-engine

yes

User defined Procedures and Functions

Triggers

yes

Callbacks using the Google Apps Engine

yes

since Access 2010 using the ACE-engine

yes

via event handler

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

yes using Neo4j Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication using Paxos

none

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Relationships in graphs

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

but no files for transaction logging

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

optionally

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

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

a simple user-level security was built in till version Access 2003

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

Specific characteristics

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

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Competitive advantages

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

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Typical application scenarios

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

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

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

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Market metrics

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

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

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

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

An Introduction to David Jones-Gilardi, Developer Relations
11 June 2024

Introducing Tejas Kumar, Developer Relations Engineer
7 June 2024

Indexing All of Wikipedia on a Laptop
5 June 2024

An Introduction to Phil Nash, Developer Relations
3 June 2024

Focus on Creativity, Not Clusters: DataStax Mission Control in Action!
30 May 2024

This Week in Neo4j: Llamaindex, Semantic Search, Graph Database, Entity Resolution and more
15 June 2024

Neo4j-Databricks Connector Delivers Deeper Insights, Faster GenAI Development
10 June 2024

This Week in Neo4j: Podcast, Testing, Knowledge Graph, GenAI and more
8 June 2024

Neo4j and Snowflake Bring Graph Data Science Into the AI Data Cloud
4 June 2024

RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph
4 June 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.