DBMS > HBase vs. Ingres vs. Lovefield vs. MySQL

System Properties Comparison HBase vs. Ingres vs. Lovefield vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Well established RDBMS

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Primary database model

Wide column store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

hbase.apache.org

www.actian.com/databases/ingres

google.github.io/lovefield

www.mysql.com

Technical documentation

hbase.apache.org/book.html

docs.actian.com/ingres

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

dev.mysql.com/doc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Actian Corporation

Google

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2008

1974

originally developed at University Berkely in early 1970s

2014

1995

Current release

2.3.4, January 2021

11.2, May 2022

2.1.12, February 2017

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

C and C++

Server operating systems

Linux
Unix
Windows

using Cygwin

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP API
Thrift

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript

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

yes

Coprocessors in Java

yes

proprietary syntax

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Ingres Replicator

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

table locks or row locks depending on storage engine

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

yes

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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