DBMS > Heroic vs. HyperSQL vs. SAP IQ vs. Vitess

System Properties Comparison Heroic vs. HyperSQL vs. SAP IQ vs. Vitess

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Columnar RDBMS optimized for Big Data analytics

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Time Series DBMS

Relational DBMS

column-oriented

Relational DBMS

Secondary database models

Document store
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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

github.com/spotify/heroic

hsqldb.org

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

vitess.io

Technical documentation

spotify.github.io/heroic

hsqldb.org/web/hsqlDocsFrame.html

help.sap.com/docs/SAP_IQ

vitess.io/docs

Developer

Spotify

SAP, formerly Sybase

The Linux Foundation, PlanetScale

Initial release

2014

2001

1994

2013

Current release

2.7.2, June 2023

16.1 SPS04, April 2019

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

based on BSD license

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

AIX
HP-UX
Linux
Solaris
Windows

Docker
Linux
macOS

Data scheme

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

with proprietary extensions

APIs and other access methods

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

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages supporting JDBC/ODBC
Java

C
C#
C++
Java
Perl
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java, SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

SAP/Sybase Replication Server

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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More resources

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