DBMS > Apache Kylin vs. HEAVY.AI vs. SiteWhere vs. Stardog

System Properties Comparison Apache Kylin vs. HEAVY.AI vs. SiteWhere vs. Stardog

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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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

M2M integration platform for persisting/querying time series data

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

kylin.apache.org

github.com/heavyai/heavydb
www.heavy.ai

github.com/sitewhere/sitewhere

www.stardog.com

Technical documentation

kylin.apache.org/docs

docs.heavy.ai

sitewhere1.sitewhere.io/index.html

docs.stardog.com

Developer

Apache Software Foundation, originally contributed from eBay Inc

HEAVY.AI, Inc.

SiteWhere

Stardog-Union

Initial release

2015

2016

2010

Current release

3.1.0, July 2020

5.10, January 2022

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Common Public Attribution License Version 1.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C++ and CUDA

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

predefined scheme

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

HTTP REST

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on HBase

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Access rights for users and roles

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More resources

Recent citations in the news

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

Introducing Kyligence Copilot: The AI Copilot for Data to Excel Your KPIs
23 August 2023, insideBIGDATA

Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

eBay's Kylin Becomes a Top-Level Apache Open Source Project
9 December 2015, eBay Inc.

How Kyligence Cloud uses Amazon EMR Serverless to simplify OLAP | Amazon Web Services
9 November 2022, AWS Blog

provided by Google News

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

Making the most of geospatial intelligence
14 April 2023, InfoWorld

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

provided by Google News

SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

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