DBMS > LokiJS vs. Snowflake vs. SpatiaLite vs. Sphinx

System Properties Comparison LokiJS vs. Snowflake vs. SpatiaLite vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

In-memory JavaScript DBMS

Cloud-based data warehousing service for structured and semi-structured data

Spatial extension of SQLite

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

github.com/techfort/LokiJS

www.snowflake.com

www.gaia-gis.it/fossil/libspatialite/index

sphinxsearch.com

Technical documentation

techfort.github.io/LokiJS

docs.snowflake.net/manuals/index.html

www.gaia-gis.it/gaia-sins/spatialite_topics.html

sphinxsearch.com/docs

Developer

Snowflake Computing Inc.

Alessandro Furieri

Sphinx Technologies Inc.

Initial release

2014

2008

2001

Current release

5.0.0, August 2020

3.5.1, February 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

GPL version 2, commercial licence available

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

JavaScript

C++

Server operating systems

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

hosted

server-less

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

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

via views

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JavaScript API

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

JavaScript

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single collection possible

ACID

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

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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