DBMS > Apache Kylin vs. FatDB vs. Graph Engine vs. JaguarDB

System Properties Comparison Apache Kylin vs. FatDB vs. Graph Engine vs. JaguarDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Relational DBMS

Document store
Key-value store

Graph DBMS
Key-value store

Key-value store
Vector DBMS

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Website

kylin.apache.org

www.graphengine.io

www.jaguardb.com

Technical documentation

kylin.apache.org/docs

www.graphengine.io/docs/manual

www.jaguardb.com/support.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

FatCloud

Microsoft

DataJaguar, Inc.

Initial release

2015

2012

2010

2015

Current release

3.1.0, July 2020

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

Open Source

GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

.NET and C

C++

the server part. Clients available in other languages

Server operating systems

Linux

Windows

.NET

Linux

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

Via inetgration in SQL Server

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

via applications

yes

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Can implement custom security layer via applications

rights management via user accounts

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More resources

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