DBMS > Apache Jena - TDB vs. Couchbase vs. Microsoft Access vs. Splice Machine

System Properties Comparison Apache Jena - TDB vs. Couchbase vs. Microsoft Access vs. Splice Machine

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Name

Description

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

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

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

RDF store

Document store

Relational DBMS

Secondary database models

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

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

jena.apache.org/documentation/tdb/index.html

www.couchbase.com

www.microsoft.com/en-us/microsoft-365/access

splicemachine.com

Technical documentation

jena.apache.org/documentation/tdb/index.html

docs.couchbase.com

developer.microsoft.com/en-us/access

splicemachine.com/how-it-works

Developer

Apache Software Foundation

originally developed by HP Labs

Couchbase, Inc.

Microsoft

Splice Machine

Initial release

2000

2011

1992

2014

Current release

4.9.0, July 2023

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

1902 (16.0.11328.20222), March 2019

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

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

commercial

Bundled with Microsoft Office

Open Source

AGPL 3.0, 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

Java

C, C++, Go and Erlang

C++

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Solaris
Windows

Data scheme

yes

RDF Schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

but not compliant to any SQL standard

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

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

ADO.NET
DAO
ODBC
OLE DB

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

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

yes

since Access 2010 using the ACE-engine

yes

Java

Triggers

yes

via event handler

yes

via the TAP protocol

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

Access control via Jena Security

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

a simple user-level security was built in till version Access 2003

Access rights for users, groups and roles according to SQL-standard

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