DBMS > LokiJS vs. Microsoft Access vs. Percona Server for MongoDB vs. Snowflake vs. Spark SQL

System Properties Comparison LokiJS vs. Microsoft Access vs. Percona Server for MongoDB vs. Snowflake vs. Spark SQL

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Name

Description

In-memory JavaScript DBMS

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.)

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

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Score	0.43
Rank	#264	Overall
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Score	104.92
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Score	0.52
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Score	121.33
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Score	18.96
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	#20	Relational DBMS

Website

github.com/techfort/LokiJS

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

www.percona.com/mongodb/software/percona-server-for-mongodb

www.snowflake.com

spark.apache.org/sql

Technical documentation

techfort.github.io/LokiJS

developer.microsoft.com/en-us/access

docs.percona.com/percona-distribution-for-mongodb

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Microsoft

Percona

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2014

1992

2015

2014

Current release

1902 (16.0.11328.20222), March 2019

3.4.10-2.10, November 2017

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

commercial

Bundled with Microsoft Office

Open Source

GPL Version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++

Scala

Server operating systems

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

Windows

Not a real database server, but making use of DLLs

Linux

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

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

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

ADO.NET
DAO
ODBC
OLE DB

proprietary protocol using JSON

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

JavaScript

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

yes

since Access 2010 using the ACE-engine

JavaScript

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

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

but no files for transaction logging

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

but no files for transaction logging

yes

In-memory capabilities

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

yes

via In-Memory Engine

User concepts

Access control

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

Access rights for users and roles

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

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