DBMS > Apache Impala vs. Faircom EDGE vs. HyperSQL vs. MySQL vs. ToroDB

System Properties Comparison Apache Impala vs. Faircom EDGE vs. HyperSQL vs. MySQL vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used open source RDBMS

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

impala.apache.org

www.faircom.com/products/faircom-edge

hsqldb.org

www.mysql.com

github.com/torodb/server

Technical documentation

impala.apache.org/impala-docs.html

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

hsqldb.org/web/hsqlDocsFrame.html

dev.mysql.com/doc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

FairCom Corporation

Oracle

since 2010, originally MySQL AB, then Sun

8Kdata

Initial release

2013

1979

2001

1995

2016

Current release

4.1.0, June 2022

V3, October 2020

2.7.2, June 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Restricted, free version available

Open Source

based on BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

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Implementation language

C++

ANSI C, C++

Java

C and C++

Java

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

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

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

string, integer, double, boolean, date, object_id

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

SQL-like DML and DDL statements

yes

ANSI SQL queries

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

All languages supporting JDBC/ODBC
Java

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

user defined functions and integration of map-reduce

yes

.Net, JavaScript, C/C++

Java, SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

table locks or row locks depending on storage engine

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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