DBMS > Apache Impala vs. Couchbase vs. FileMaker vs. IBM Db2 vs. RDF4J

System Properties Comparison Apache Impala vs. Couchbase vs. FileMaker vs. IBM Db2 vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Common in IBM host environments, 2 different versions for host and Windows/Linux

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

RDF store

Secondary database models

Document store

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

impala.apache.org

www.couchbase.com

www.claris.com/filemaker

www.ibm.com/products/db2

rdf4j.org

Technical documentation

impala.apache.org/impala-docs.html

docs.couchbase.com

www.claris.com/resources/documentation

www.ibm.com/docs/en/db2

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Couchbase, Inc.

Claris

a subsidiary of Apple

IBM

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2013

2011

1983

host version

2004

Current release

4.1.0, June 2022

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

19.4.1, November 2021

12.1, October 2016

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++

C, C++, Go and Erlang

C and C++

Java

Server operating systems

Linux

Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

via plugins

yes

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Filemaker WebDirect
JDBC
ODBC

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

PHP

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

Sharding

only with Windows/Unix/Linux Version

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication, warm standby

since Version 14

yes

with separate tools (MQ, InfoSphere)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

simple rights management via user accounts and connection to external directory services

fine grained access rights according to SQL-standard

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