DBMS > Apache Kylin vs. Bangdb vs. H2 vs. Netezza

System Properties Comparison Apache Kylin vs. Bangdb vs. H2 vs. Netezza

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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

Converged and high performance database for device data, events, time series, document and graph

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

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	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Website

kylin.apache.org

bangdb.com

www.h2database.com

www.ibm.com/products/netezza

Technical documentation

kylin.apache.org/docs

docs.bangdb.com

www.h2database.com/html/main.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

Sachin Sinha, BangDB

Thomas Mueller

IBM

Initial release

2015

2012

2005

2000

Current release

3.1.0, July 2020

BangDB 2.0, October 2021

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD 3

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

Java

Server operating systems

Linux

All OS with a Java VM

Linux

included in appliance

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SQL like support with command line tool

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol
RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
Python

Java

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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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

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, ibm.com

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, Microsoft

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

provided by Google News

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