DBMS > etcd vs. Google Cloud Firestore vs. NCache vs. RDF4J vs. Yanza

System Properties Comparison etcd vs. Google Cloud Firestore vs. NCache vs. RDF4J vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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.

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

etcd.io
github.com/etcd-io/etcd

firebase.google.com/products/firestore

www.alachisoft.com/ncache

rdf4j.org

yanza.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

firebase.google.com/docs/firestore

www.alachisoft.com/resources/docs

rdf4j.org/documentation

Developer

Google

Alachisoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Yanza

Initial release

2017

2005

2004

2015

Current release

3.4, August 2019

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Enterprise Edition available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C#, .NET, .NET Core, Java

Java

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

Linux
Windows

Linux
OS X
Unix
Windows

Windows

Data scheme

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

partial

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

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

yes

SQL

Support of SQL

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

APIs and other access methods

gRPC
JSON over HTTP

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

IDistributedCache
JCache
LINQ
Proprietary native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

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

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

Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

support for stored procedures with SQL-Server CLR

yes

Triggers

yes, watching key changes

yes, with Cloud Functions

yes

Notifications

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

optimistic locking and pessimistic locking

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

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

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.

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