DBMS > Heroic vs. Infobright vs. SAP HANA vs. Transwarp Hippo

System Properties Comparison Heroic vs. Infobright vs. SAP HANA vs. Transwarp Hippo

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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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Time Series DBMS

Relational DBMS

Vector DBMS

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	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

github.com/spotify/heroic

ignitetech.com/softwarelibrary/infobrightdb

www.sap.com/products/hana.html

www.transwarp.cn/en/subproduct/hippo

Technical documentation

spotify.github.io/heroic

help.sap.com/hana

Developer

Spotify

Ignite Technologies Inc.; formerly InfoBright Inc.

SAP

Initial release

2014

2005

2010

2023

Current release

2.0 SPS07 (April 4, 2023), April 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Linux
Windows

Appliance or cloud-service

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

Knowledge Grid Technology used instead

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

JDBC
ODBC

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java
Python

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

yes

Role based access control and fine grained access rights

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