DBMS > Apache Kylin vs. Bangdb vs. LokiJS vs. MonetDB vs. STSdb

System Properties Comparison Apache Kylin vs. Bangdb vs. LokiJS vs. MonetDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Converged and high performance database for device data, events, time series, document and graph

In-memory JavaScript DBMS

A relational database management system that stores data in columns

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

kylin.apache.org

bangdb.com

github.com/techfort/LokiJS

www.monetdb.org

github.com/STSSoft/STSdb4

Technical documentation

kylin.apache.org/docs

docs.bangdb.com

techfort.github.io/LokiJS

www.monetdb.org/Documentation

Developer

Apache Software Foundation, originally contributed from eBay Inc

Sachin Sinha, BangDB

MonetDB BV

STS Soft SC

Initial release

2015

2012

2014

2004

2011

Current release

3.1.0, July 2020

BangDB 2.0, October 2021

Dec2023 (11.49), December 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD 3

Open Source

Mozilla Public License 2.0

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

JavaScript

Server operating systems

Linux

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

FreeBSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

primitive types and user defined types (classes)

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

secondary, composite, nested, reverse, geospatial

yes

via views

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SQL like support with command line tool

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol
RESTful HTTP API

JavaScript API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

.NET Client API

Supported programming languages

C
C#
C++
Java
Python

JavaScript

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C#
Java

Server-side scripts

Stored procedures

View functions in JavaScript

yes, in SQL, C, R

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

Source-replica replication available in experimental status

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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