DBMS > GeoSpock vs. MongoDB vs. RDF4J vs. RDFox vs. TDengine

System Properties Comparison GeoSpock vs. MongoDB vs. RDF4J vs. RDFox vs. TDengine

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

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

High performance knowledge graph and semantic reasoning engine

Time Series DBMS and big data platform

Primary database model

Secondary database models

Time Series DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Relational DBMS

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

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

geospock.com

www.mongodb.com

rdf4j.org

www.oxfordsemantic.tech

github.com/taosdata/TDengine
tdengine.com

Technical documentation

www.mongodb.com/docs/manual

rdf4j.org/documentation

docs.oxfordsemantic.tech

docs.tdengine.com

Developer

GeoSpock

MongoDB, Inc

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

Oxford Semantic Technologies

TDEngine, previously Taos Data

Initial release

2009

2004

2017

2019

Current release

2.0, September 2019

6.0.7, June 2023

6.0, Septermber 2022

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

AGPL V3, also commercial editions available

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

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Implementation language

Java, Javascript

C++

Java

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Linux
Windows

Data scheme

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

RDF Schemas

yes

RDF schemas

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

Read-only SQL queries via the MongoDB Atlas SQL Interface

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API
SPARQL 1.1

JDBC
RESTful HTTP API

Supported programming languages

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Java
PHP
Python

C
Java

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

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

yes

in MongoDB Atlas only

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

none

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Access rights for users can be defined per table

Access rights for users and roles

Roles, resources, and access types

yes

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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TDengine OSS is an open source, cloud native time series database. It includes built-in...
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News

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31 May 2024

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.