DBMS > Apache Impala vs. Firebird vs. LeanXcale vs. Memcached vs. Oracle Berkeley DB

System Properties Comparison Apache Impala vs. Firebird vs. LeanXcale vs. Memcached vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

In-memory key-value store, originally intended for caching

Widely used in-process key-value store

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

impala.apache.org/impala-docs.html

www.firebirdsql.org/en/reference-manuals

github.com/memcached/memcached/wiki

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Firebird Foundation

LeanXcale

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2013

2000

As fork of Borland's InterBase

2015

2003

1994

Current release

4.1.0, June 2022

5.0.0, January 2024

1.6.27, May 2024

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Initial Developer's Public License

commercial

Open Source

BSD license

Open Source

commercial license 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, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

FreeBSD
Linux
OS X
Unix
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

through Apache Derby

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
Java
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PSQL

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

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

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

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

Users with fine-grained authorization concept

yes

using SASL (Simple Authentication and Security Layer) protocol

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