DBMS > Apache Impala vs. H2 vs. MySQL vs. NSDb vs. OpenEdge

System Properties Comparison Apache Impala vs. H2 vs. MySQL vs. NSDb vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Widely used open source RDBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Application development environment with integrated database management system

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store

Spatial DBMS

Document store
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Website

www.progress.com/openedge

Technical documentation

impala.apache.org/impala-docs.html

www.h2database.com/html/main.html

dev.mysql.com/doc

nsdb.io/Architecture

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Thomas Mueller

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Initial release

2013

2005

1995

2017

1984

Current release

4.1.0, June 2022

2.2.220, July 2023

8.4.0, April 2024

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C and C++

Java, Scala

Server operating systems

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language

yes

close to SQL 92

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
HTTP REST
WebSocket

JDBC
ODBC

Supported programming languages

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

Java
Scala

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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 access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Users and groups

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