DBMS > Apache Impala vs. Firebird vs. MarkLogic

System Properties Comparison Apache Impala vs. Firebird vs. MarkLogic

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Operational and transactional Enterprise NoSQL database

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Website

impala.apache.org

www.firebirdsql.org

www.marklogic.com

Technical documentation

impala.apache.org/impala-docs.html

www.firebirdsql.org/en/reference-manuals

docs.marklogic.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Firebird Foundation

MarkLogic Corp.

Initial release

2013

2000

As fork of Borland's InterBase

2001

Current release

4.1.0, June 2022

5.0.0, January 2024

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Initial Developer's Public License

commercial

restricted free version is available

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

C++

C and C++

C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

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

SQL-like DML and DDL statements

yes

SQL92

APIs and other access methods

JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PSQL

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

yes

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

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, with Range Indexes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authorization concept

Role-based access control at the document and subdocument levels

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

12 Top Open Source Databases to Consider
1 May 2024, TechTarget

DoNot Team's New Firebird Backdoor Hits Pakistan and Afghanistan
23 October 2023, The Hacker News

How to Run Multiple Instances of Firebird Server - opensource for you
31 August 2019, Open Source For You

Top 15 Databases to Use in 2024 and Beyond
4 June 2021, Appinventiv

EF Core Database Providers
4 January 2019, InfoQ.com

provided by Google News

MarkLogic “The NoSQL Database”. In the MarkLogic Query Console, you can… | by Abhay Srivastava | Apr, 2024
22 April 2024, Medium

AI can make logistics data as valuable as intelligence or operational data for mission success
17 April 2024, Breaking Defense

Database Platform to Simplify Complex Data | Progress Marklogic
7 February 2023, Progress Software

ABN AMRO Moves Progress-Powered Credit Store App to Azure Cloud; Achieves 40% Faster Data Processing, Lower ...
12 March 2024, GlobeNewswire

Seven Quick Steps to Setting Up MarkLogic Server in Kubernetes
1 February 2024, release.nl

provided by Google News

Share this page