DBMS > Heroic vs. Hive vs. SAP HANA vs. SWC-DB

System Properties Comparison Heroic vs. Hive vs. SAP HANA vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

A high performance, scalable Wide Column DBMS

Primary database model

Time Series DBMS

Relational DBMS

Wide column store

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Time Series DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

github.com/spotify/heroic

hive.apache.org

www.sap.com/products/hana.html

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

spotify.github.io/heroic

cwiki.apache.org/confluence/display/Hive/Home

help.sap.com/hana

Developer

Spotify

Apache Software Foundation

initially developed by Facebook

SAP

Alex Kashirin

Initial release

2014

2012

2010

2020

Current release

3.1.3, April 2022

2.0 SPS07 (April 4, 2023), April 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

Open Source

GPL V3

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

All OS with a Java VM

Appliance or cloud-service

Linux

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

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

JDBC
ODBC
Thrift

JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

C++
Java
PHP
Python

C++

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

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

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 rights for users, groups and roles

yes

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