DBMS > Apache Kylin vs. Heroic vs. IBM Cloudant vs. Microsoft SQL Server

System Properties Comparison Apache Kylin vs. Heroic vs. IBM Cloudant vs. Microsoft SQL Server

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Database as a Service offering based on Apache CouchDB

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

kylin.apache.org

github.com/spotify/heroic

www.ibm.com/products/cloudant

www.microsoft.com/en-us/sql-server

Technical documentation

kylin.apache.org/docs

spotify.github.io/heroic

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/en-US/sql/sql-server

Developer

Apache Software Foundation, originally contributed from eBay Inc

Spotify

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Initial release

2015

2014

2010

1989

Current release

3.1.0, July 2020

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

C++

Server operating systems

Linux

hosted

Linux
Windows

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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.