DBMS > HBase vs. Kyligence Enterprise vs. Microsoft SQL Server vs. ReductStore vs. SAP SQL Anywhere

System Properties Comparison HBase vs. Kyligence Enterprise vs. Microsoft SQL Server vs. ReductStore vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

A distributed analytics engine for big data, built on top of Apache Kylin

Microsofts flagship relational DBMS

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

hbase.apache.org

kyligence.io/kyligence-enterprise

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

github.com/reductstore
www.reduct.store

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

hbase.apache.org/book.html

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

www.reduct.store/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Kyligence, Inc.

Microsoft

ReductStore LLC

SAP

formerly Sybase

Initial release

2008

2016

1989

2023

1992

Current release

2.3.4, January 2021

SQL Server 2022, November 2022

1.9, March 2024

17, July 2015

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

Business Source License 1.1

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

C++, Rust

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux

Linux
Windows

Docker
Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
RESTful HTTP API

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

HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C++
JavaScript (Node.js)
Python
Rust

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

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

yes, in C/C++, Java, .Net or Perl

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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