DBMS > Apache Doris vs. Apache Impala vs. Firebird vs. H2GIS

System Properties Comparison Apache Doris vs. Apache Impala vs. Firebird vs. H2GIS

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Analytic DBMS for Hadoop

Firebird is an open source RDBMS forked from Borland's InterBase

Spatial extension of H2

Primary database model

Relational DBMS

Spatial DBMS

Secondary database models

Document store

Relational DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Website

doris.apache.org
github.com/apache/doris

impala.apache.org

www.firebirdsql.org

www.h2gis.org

Technical documentation

github.com/apache/doris/wiki

impala.apache.org/impala-docs.html

www.firebirdsql.org/en/reference-manuals

www.h2gis.org/docs/home

Developer

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Firebird Foundation

CNRS

Initial release

2017

2013

2000

As fork of Borland's InterBase

2013

Current release

1.2.2, February 2023

4.1.0, June 2022

5.0.0, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

Initial Developer's Public License

Open Source

LGPL 3.0

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++

C and C++

Java

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Supported programming languages

Java

All languages supporting JDBC/ODBC

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

PSQL

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Source-replica replication

yes

based on H2

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

Immediate Consistency

Eventual 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

Features a multi-generational MVCC architecture, readers do not block writers

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authorization concept

yes

based on H2

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More resources

Recent citations in the news

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5 June 2024, hackernoon.com

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
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1 September 2023, KDnuggets

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24 June 2022, InfoWorld

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12 March 2017, Uber

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