DBMS > Apache Kylin vs. EJDB vs. MonetDB vs. Snowflake vs. Valentina Server

System Properties Comparison Apache Kylin vs. EJDB vs. MonetDB vs. Snowflake vs. Valentina Server

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A relational database management system that stores data in columns

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

Object-relational database and reports server

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

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	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

kylin.apache.org

github.com/Softmotions/ejdb

www.monetdb.org

www.snowflake.com

www.valentina-db.net

Technical documentation

kylin.apache.org/docs

github.com/Softmotions/ejdb/blob/master/README.md

www.monetdb.org/Documentation

docs.snowflake.net/manuals/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Apache Software Foundation, originally contributed from eBay Inc

Softmotions

MonetDB BV

Snowflake Computing Inc.

Paradigma Software

Initial release

2015

2012

2004

2014

1999

Current release

3.1.0, July 2020

Dec2023 (11.49), December 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2

Open Source

Mozilla Public License 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux

server-less

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL 2003 with some extensions

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

in-process shared library

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

CLI Client
JDBC
ODBC

ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

JavaScript (Node.js)
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes, in SQL, C, R

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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