DBMS > Datomic vs. Google BigQuery vs. NCache vs. NSDb vs. SiteWhere

System Properties Comparison Datomic vs. Google BigQuery vs. NCache vs. NSDb vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Large scale data warehouse service with append-only tables

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

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

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

www.datomic.com

cloud.google.com/bigquery

www.alachisoft.com/ncache

nsdb.io

github.com/sitewhere/sitewhere

Technical documentation

docs.datomic.com

cloud.google.com/bigquery/docs

www.alachisoft.com/resources/docs

nsdb.io/Architecture

sitewhere1.sitewhere.io/index.html

Developer

Cognitect

Google

Alachisoft

SiteWhere

Initial release

2012

2010

2005

2017

2010

Current release

1.0.7075, December 2023

5.3.3, April 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Enterprise Edition available

Open Source

Apache Version 2.0

Open Source

Common Public Attribution License Version 1.0

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.

Implementation language

Java, Clojure

C#, .NET, .NET Core, Java

Java, Scala

Java

Server operating systems

All OS with a Java VM

hosted

Linux
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

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

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

all fields are automatically indexed

SQL

Support of SQL

yes

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 API

RESTful HTTP/JSON API

IDistributedCache
JCache
LINQ
Proprietary native API

gRPC
HTTP REST
WebSocket

HTTP REST

Supported programming languages

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Java
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

support for stored procedures with SQL-Server CLR

Triggers

By using transaction functions

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes, with selectable consistency level

selectable replication factor

based on HBase

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

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

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

Users with fine-grained authorization concept

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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