DBMS > Google BigQuery vs. Microsoft Access vs. NCache vs. NSDb vs. SwayDB

System Properties Comparison Google BigQuery vs. Microsoft Access vs. NCache vs. NSDb vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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.)

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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	50.03
Rank	#24	Overall
	#16	Relational DBMS

Score	146.50
Rank	#9	Overall
	#6	Relational DBMS

Score	0.90
Rank	#186	Overall
	#31	Key-value stores

Score	0.00
Rank	#357	Overall
	#33	Time Series DBMS

Score	0.01
Rank	#349	Overall
	#53	Key-value stores

Website

cloud.google.com/bigquery

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

www.alachisoft.com/ncache

nsdb.io

swaydb.io

Technical documentation

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

www.alachisoft.com/resources/docs

nsdb.io/Architecture

Developer

Google

Microsoft

Alachisoft

Simer Plaha

Initial release

2010

1992

2005

2017

2018

Current release

1902 (16.0.11328.20222), March 2019

5.2, April 2021

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

Enterprise Edition available

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

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.

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Implementation language

C++

C#, .NET, .NET Core, Java

Java, Scala

Scala

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

Linux
Windows

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

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

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

but not compliant to any SQL standard

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

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

IDistributedCache
JCache
LINQ
Proprietary native API

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Visual Basic.NET

Java
Scala

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

support for stored procedures with SQL-Server CLR

Triggers

yes

since Access 2010 using the ACE-engine

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

optimistic locking and pessimistic locking

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

Using Apache Lucene

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

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...
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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.
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Licensing and pricing models

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

NCache at Atlanta .NET User Group Meetup 2017
1 July 2022

SDD Conference 2017, London – Scaling .NET Apps with Distributed Cache
1 July 2022

Quickstart: NCache Python Client
20 June 2022

Scaling Full Text Indexing Using NCache Distributed Lucene
10 June 2022

Session Storage in ASP.NET Core Using NCache
3 June 2022

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