DBMS > Apache Jena - TDB vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. Qdrant vs. TerarkDB

System Properties Comparison Apache Jena - TDB vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. Qdrant vs. TerarkDB

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

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

A high-performance vector database with neural network or semantic-based matching

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

RDF store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Vector DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	2.75
Rank	#104	Overall
	#19	Document stores

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

Score	1.28
Rank	#167	Overall
	#8	Vector DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

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

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

github.com/qdrant/qdrant
qdrant.tech

github.com/bytedance/terarkdb

Technical documentation

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

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

qdrant.tech/documentation

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

originally developed by HP Labs

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Qdrant

ByteDance, originally Terark

Initial release

2000

2010

2014

2021

2016

Current release

4.9.0, July 2023

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

Open Source

Apache Version 2.0

commercial

restricted open source version available

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

Erlang

Rust

C++

Server operating systems

All OS with a Java VM

hosted

Docker
Linux
macOS
Windows

Data scheme

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

JSON types

Numbers, Strings, Geo, Boolean

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

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

RESTful HTTP/JSON API

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

C++ API
Java API

Supported programming languages

Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C++
Java

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

JavaScript

Triggers

yes

via event handler

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

Collection-level replication

none

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

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

TDB Transactions

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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 database

Access rights can be defined down to the item level

Key-based authentication

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