DBMS > Apache Kylin vs. EJDB vs. MonetDB vs. ObjectBox vs. Snowflake

System Properties Comparison Apache Kylin vs. EJDB vs. MonetDB vs. ObjectBox vs. Snowflake

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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	1.14
Rank	#171	Overall
	#77	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

kylin.apache.org

github.com/Softmotions/ejdb

www.monetdb.org

github.com/objectbox
objectbox.io

www.snowflake.com

Technical documentation

kylin.apache.org/docs

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

www.monetdb.org/Documentation

docs.objectbox.io

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

Softmotions

MonetDB BV

ObjectBox Limited

Snowflake Computing Inc.

Initial release

2015

2012

2004

2017

2014

Current release

3.1.0, July 2020

Dec2023 (11.49), December 2023

4.0 (May 2024)

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2

Open Source

Mozilla Public License 2.0

Bindings are released under Apache 2.0

Apache License 2.0

commercial

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

Java

C and C++

Server operating systems

Linux

server-less

FreeBSD
Linux
OS X
Solaris
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

yes, plus "flex" map-like types

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

Proprietary native API

CLI Client
JDBC
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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, in SQL, C, R

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Data sync between devices allowing occasional connected databases to work completely offline

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.