DBMS > Google BigQuery vs. JaguarDB vs. LokiJS vs. NCache vs. PouchDB

System Properties Comparison Google BigQuery vs. JaguarDB vs. LokiJS vs. NCache vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Performant, highly scalable DBMS for AI and IoT applications

In-memory JavaScript DBMS

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

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store

Key-value store

Document store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

cloud.google.com/bigquery

www.jaguardb.com

github.com/techfort/LokiJS

www.alachisoft.com/ncache

pouchdb.com

Technical documentation

cloud.google.com/bigquery/docs

www.jaguardb.com/support.html

techfort.github.io/LokiJS

www.alachisoft.com/resources/docs

pouchdb.com/guides

Developer

Google

DataJaguar, Inc.

Alachisoft

Apache Software Foundation

Initial release

2010

2015

2014

2005

2012

Current release

3.3 July 2023

5.3.3, April 2024

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

Enterprise Edition available

Open Source

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++

the server part. Clients available in other languages

JavaScript

C#, .NET, .NET Core, Java

JavaScript

Server operating systems

hosted

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

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

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

via views

yes

via views

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

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

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

JavaScript API

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions in JavaScript

support for stored procedures with SQL-Server CLR

View functions in JavaScript

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes, with selectable consistency level

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

none

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

atomic operations within a single collection possible

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

by using IndexedDB, WebSQL or LevelDB as backend

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)

rights management via user accounts

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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