DBMS > Apache Kylin vs. Graph Engine vs. HEAVY.AI vs. Infobright

System Properties Comparison Apache Kylin vs. Graph Engine vs. HEAVY.AI vs. Infobright

Please select another system to include it in the comparison.

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

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.14
Rank	#171	Overall
	#77	Relational DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Website

kylin.apache.org

www.graphengine.io

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

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

kylin.apache.org/docs

www.graphengine.io/docs/manual

docs.heavy.ai

Developer

Apache Software Foundation, originally contributed from eBay Inc

Microsoft

HEAVY.AI, Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2015

2010

2016

2005

Current release

3.1.0, July 2020

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

Apache Version 2; enterprise edition available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

.NET and C

C++ and CUDA

Server operating systems

Linux

.NET

Linux

Linux
Windows

Data scheme

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

Knowledge Grid Technology used instead

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

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

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

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

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

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

Distributed OLAPer Kyligence accelerates core engine, adds real-time data support
10 August 2021, Blocks & Files

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

provided by Google News

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019
27 February 2019, Data Science Central

provided by Google News

5 Q’s for Mike Flaxman, Vice President of Heavy.AI
15 August 2024, Center for Data Innovation

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series
19 September 2024, Unite.AI

HEAVY.AI Accelerates Big Data Analytics with Vultr's High-Performance GPU Cloud Infrastructure
11 September 2024, insideBIGDATA

HEAVY.AI Accelerates Big Data Analytics with Vultr’s High-Performance GPU Cloud Infrastructure
11 September 2024, insideBIGDATA

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

provided by Google News

Share this page