DBMS > Apache Jena - TDB vs. Datastax Enterprise vs. JaguarDB vs. Microsoft Azure Cosmos DB

System Properties Comparison Apache Jena - TDB vs. Datastax Enterprise vs. JaguarDB vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Description

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

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Performant, highly scalable DBMS for AI and IoT applications

Globally distributed, horizontally scalable, multi-model database service

Primary database model

RDF store

Wide column store

Key-value store
Vector DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Spatial DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

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

www.datastax.com/products/datastax-enterprise

www.jaguardb.com

azure.microsoft.com/services/cosmos-db

Technical documentation

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

docs.datastax.com

www.jaguardb.com/support.html

learn.microsoft.com/azure/cosmos-db

Developer

Apache Software Foundation

originally developed by HP Labs

DataStax

DataJaguar, Inc.

Microsoft

Initial release

2000

2011

2015

2014

Current release

4.9.0, July 2023

6.8, April 2020

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

Open Source

GPL V3.0

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.

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Implementation language

Java

C++

the server part. Clients available in other languages

Server operating systems

All OS with a Java VM

Linux
OS X

Linux

hosted

Data scheme

yes

RDF Schemas

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Java

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

via event handler

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

configurable replication factor, datacenter aware, advanced replication for edge computing

Multi-source replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

TDB Transactions

Atomicity and isolation are supported for single operations

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights for users can be defined per object

rights management via user accounts

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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