DBMS > Google Cloud Datastore vs. NCache vs. Oracle Rdb vs. VoltDB

System Properties Comparison Google Cloud Datastore vs. NCache vs. Oracle Rdb vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Key-value store

Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

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

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

cloud.google.com/datastore

www.alachisoft.com/ncache

www.oracle.com/database/technologies/related/rdb.html

www.voltdb.com

Technical documentation

cloud.google.com/datastore/docs

www.alachisoft.com/resources/docs

www.oracle.com/database/technologies/related/rdb-doc.html

docs.voltdb.com

Developer

Google

Alachisoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

VoltDB Inc.

Initial release

2008

2005

1984

2010

Current release

5.3.3, April 2024

7.4.1.1, 2021

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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.

Implementation language

C#, .NET, .NET Core, Java

Java, C++

Server operating systems

hosted

Linux
Windows

HP Open VMS

Linux
OS X

for development

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

yes, details here

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 language (GQL)

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

yes

only a subset of SQL 99

APIs and other access methods

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

IDistributedCache
JCache
LINQ
Proprietary native API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

using Google App Engine

support for stored procedures with SQL-Server CLR

Java

Triggers

Callbacks using the Google Apps Engine

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes, with selectable consistency level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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.

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

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

optimistic locking and pessimistic locking

yes, on a single node

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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 (IAM)

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

Users and roles with access to stored procedures

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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