DBMS > Heroic vs. Microsoft SQL Server vs. SAP HANA vs. Tkrzw vs. Ultipa

System Properties Comparison Heroic vs. Microsoft SQL Server vs. SAP HANA vs. Tkrzw vs. Ultipa

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

github.com/spotify/heroic

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

www.sap.com/products/hana.html

dbmx.net/tkrzw

www.ultipa.com

Technical documentation

spotify.github.io/heroic

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

help.sap.com/hana

www.ultipa.com/document

Developer

Spotify

Microsoft

SAP

Mikio Hirabayashi

Ultipa

Initial release

2014

1989

2010

2020

2019

Current release

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

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

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Implementation language

Java

C++

Server operating systems

Linux
Windows

Appliance or cloud-service

Linux
macOS

Data scheme

schema-free

yes

schema-free

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

yes

APIs and other access methods

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

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

JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

C++
Java
Python
Ruby

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

SQLScript, R

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

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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