DBMS > Hive vs. LokiJS vs. Sadas Engine vs. SWC-DB

System Properties Comparison Hive vs. LokiJS vs. Sadas Engine vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

In-memory JavaScript DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Time Series DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

hive.apache.org

github.com/techfort/LokiJS

www.sadasengine.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

techfort.github.io/LokiJS

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

initially developed by Facebook

SADAS s.r.l.

Alex Kashirin

Initial release

2012

2014

2006

2020

Current release

3.1.3, April 2022

8.0

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

commercial

free trial version available

Open Source

GPL V3

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

Java

JavaScript

C++

Server operating systems

All OS with a Java VM

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

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift

JavaScript API

JDBC
ODBC
Proprietary protocol

Proprietary protocol
Thrift

Supported programming languages

C++
Java
PHP
Python

JavaScript

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

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

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

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