DBMS > Derby vs. HEAVY.AI vs. Lovefield vs. SAP IQ

System Properties Comparison Derby vs. HEAVY.AI vs. Lovefield vs. SAP IQ

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

column-oriented

Secondary database models

Spatial DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

db.apache.org/derby

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

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

Technical documentation

db.apache.org/derby/manuals/index.html

docs.heavy.ai

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

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

HEAVY.AI, Inc.

Google

SAP, formerly Sybase

Initial release

1997

2016

2014

1994

Current release

10.17.1.0, November 2023

5.10, January 2022

2.1.12, February 2017

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; enterprise edition available

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

C++ and CUDA

JavaScript

Server operating systems

All OS with a Java VM

Linux

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

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

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

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

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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