DBMS > Apache Jena - TDB vs. Badger vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

System Properties Comparison Apache Jena - TDB vs. Badger vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A Wide Column Store for rapid development using massive semi-structured datasets

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

RDF store

Key-value store

Document store
Key-value store

Wide column store

Relational DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

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

github.com/dgraph-io/badger

azure.microsoft.com/en-us/services/storage/tables

yaacomo.com

Technical documentation

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

godoc.org/github.com/dgraph-io/badger

Developer

Apache Software Foundation

originally developed by HP Labs

DGraph Labs

FatCloud

Microsoft

Q2WEB GmbH

Initial release

2000

2017

2012

2009

Current release

4.9.0, July 2023

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

All OS with a Java VM

BSD
Linux
OS X
Solaris
Windows

Windows

hosted

Android
Linux
Windows

Data scheme

yes

RDF Schemas

schema-free

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

Via inetgration in SQL Server

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

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

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via event handler

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

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 control via Jena Security

Can implement custom security layer via applications

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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

Sparql Secrets In Jena-Fuseki - DataScienceCentral.com
24 July 2022, Data Science Central

Extract and query knowledge graphs using Apache Jena (SPARQL Engine)
4 December 2019, Towards Data Science

6 Java Libraries for Machine Learning – AIM
3 October 2023, Analytics India Magazine

A catalogue with semantic annotations makes multilabel datasets FAIR | Scientific Reports
4 May 2022, Nature.com

MarkLogic Hones Its Triple Store
18 August 2015, Datanami

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

Quick Guide to Azure Storage Pricing
16 May 2023, DevOps.com

Inside Azure File Storage
7 October 2015, azure.microsoft.com

provided by Google News

Share this page