DBMS > Lovefield vs. NCache vs. ObjectBox vs. Sphinx

System Properties Comparison Lovefield vs. NCache vs. ObjectBox vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

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

Extremely fast embedded database for small devices, IoT and Mobile

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

Time Series DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

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

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

google.github.io/lovefield

www.alachisoft.com/ncache

objectbox.io

sphinxsearch.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

www.alachisoft.com/resources/docs

docs.objectbox.io

sphinxsearch.com/docs

Developer

Google

Alachisoft

ObjectBox Limited

Sphinx Technologies Inc.

Initial release

2014

2005

2017

2001

Current release

2.1.12, February 2017

5.3.3, April 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Enterprise Edition available

Open Source

Apache License 2.0

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C#, .NET, .NET Core, Java

C and C++

C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Android
iOS
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

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

SQL-like query language (SphinxQL)

APIs and other access methods

IDistributedCache
JCache
LINQ
Proprietary native API

Proprietary native API

Proprietary protocol

Supported programming languages

JavaScript

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

Triggers

Using read-only observers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

none

yes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

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

yes

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

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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