DBMS > AnzoGraph DB vs. Google Cloud Firestore vs. H2 vs. NCache

System Properties Comparison AnzoGraph DB vs. Google Cloud Firestore vs. H2 vs. NCache

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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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Open-Source and Enterprise in-memory Key-Value Store

Primary database model

Secondary database models

Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Website

cambridgesemantics.com/anzograph

firebase.google.com/products/firestore

www.h2database.com

www.alachisoft.com/ncache

Technical documentation

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

firebase.google.com/docs/firestore

www.h2database.com/html/main.html

www.alachisoft.com/resources/docs

Developer

Cambridge Semantics

Google

Thomas Mueller

Alachisoft

Initial release

2018

2017

2005

Current release

2.3, January 2021

2.2.220, July 2023

5.3.3, April 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Enterprise Edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C#, .NET, .NET Core, Java

Server operating systems

Linux

hosted

All OS with a Java VM

Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

yes

SQL

Support of SQL

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

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

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

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

C++
Java
Python

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Java

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

yes, Firebase Rules & Cloud Functions

Java Stored Procedures and User-Defined Functions

support for stored procedures with SQL-Server CLR

Triggers

yes, with Cloud Functions

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

yes

ACID

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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 and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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