DBMS > Apache Kylin vs. FeatureBase vs. SAP HANA vs. SQream DB

System Properties Comparison Apache Kylin vs. FeatureBase vs. SAP HANA vs. SQream DB

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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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

In-memory, column based data store. Available as appliance or cloud service

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

kylin.apache.org

www.featurebase.com

www.sap.com/products/hana.html

sqream.com

Technical documentation

kylin.apache.org/docs

docs.featurebase.com

help.sap.com/hana

docs.sqream.com

Developer

Apache Software Foundation, originally contributed from eBay Inc

Molecula and Pilosa Open Source Contributors

SAP

SQream Technologies

Initial release

2015

2017

2010

2017

Current release

3.1.0, July 2020

2022, May 2022

2.0 SPS07 (April 4, 2023), April 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Linux
macOS

Appliance or cloud-service

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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)

SQL queries

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Java
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

SQLScript, R

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

yes

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