DBMS > Heroic vs. SAP HANA vs. Tkrzw vs. Transwarp KunDB

System Properties Comparison Heroic vs. SAP HANA vs. Tkrzw vs. Transwarp KunDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

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	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

github.com/spotify/heroic

www.sap.com/products/hana.html

dbmx.net/tkrzw

www.transwarp.cn/en/product/kundb

Technical documentation

spotify.github.io/heroic

help.sap.com/hana

Developer

Spotify

SAP

Mikio Hirabayashi

Transwarp

Initial release

2014

2010

2020

Current release

2.0 SPS07 (April 4, 2023), April 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

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

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

Implementation language

Java

C++

Server operating systems

Appliance or cloud-service

Linux
macOS

Data scheme

schema-free

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.

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

JDBC
ODBC

Supported programming languages

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

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.