DBMS > atoti vs. Google Cloud Datastore vs. NCache vs. searchxml

System Properties Comparison atoti vs. Google Cloud Datastore vs. NCache vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Object oriented DBMS

Document store

Key-value store

Native XML DBMS
Search engine

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	0.59
Rank	#242	Overall
	#10	Object oriented DBMS

Score	4.49
Rank	#79	Overall
	#12	Document stores

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

atoti.io

cloud.google.com/datastore

www.alachisoft.com/ncache

www.searchxml.net/category/products

Technical documentation

docs.atoti.io

cloud.google.com/datastore/docs

www.alachisoft.com/resources/docs

www.searchxml.net/support/handouts

Developer

ActiveViam

Google

Alachisoft

informationpartners gmbh

Initial release

2008

2005

2015

Current release

5.3.3, April 2024

1.0

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Enterprise Edition 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.

Implementation language

Java

C#, .NET, .NET Core, Java

C++

Server operating systems

hosted

Linux
Windows

Windows

Data scheme

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language (GQL)

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

APIs and other access methods

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

IDistributedCache
JCache
LINQ
Proprietary native API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

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

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Python

using Google App Engine

support for stored procedures with SQL-Server CLR

yes

on the application server

Triggers

Callbacks using the Google Apps Engine

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes, with selectable consistency level

yes

sychronisation to multiple collections

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

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

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

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, 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)

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
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Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
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Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
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Key customers

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