DBMS > Heroic vs. Ingres vs. Lovefield vs. SAP IQ

System Properties Comparison Heroic vs. Ingres vs. Lovefield vs. SAP IQ

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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

Well established RDBMS

Embeddable relational database for web apps written in pure JavaScript

Columnar RDBMS optimized for Big Data analytics

Primary database model

Time Series DBMS

Relational DBMS

column-oriented

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

github.com/spotify/heroic

www.actian.com/databases/ingres

google.github.io/lovefield

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

Technical documentation

spotify.github.io/heroic

docs.actian.com/ingres

github.com/google/lovefield/blob/master/docs/spec_index.md

help.sap.com/docs/SAP_IQ

Developer

Spotify

Actian Corporation

Google

SAP, formerly Sybase

Initial release

2014

1974

originally developed at University Berkely in early 1970s

2014

1994

Current release

11.2, May 2022

2.1.12, February 2017

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

commercial

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

JavaScript

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

JavaScript

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Ingres Replicator

none

SAP/Sybase Replication Server

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

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

MVCC

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

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