DBMS > GeoSpock vs. GreptimeDB vs. MongoDB vs. RDF4J vs. Vitess

System Properties Comparison GeoSpock vs. GreptimeDB vs. MongoDB vs. RDF4J vs. Vitess

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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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.

Scalable, distributed, cloud-native DBMS, extending MySQL

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

Document store
Spatial DBMS

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

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

geospock.com

Technical documentation

docs.greptime.com

www.mongodb.com/docs/manual

rdf4j.org/documentation

vitess.io/docs

Developer

GeoSpock

Greptime Inc.

MongoDB, Inc

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

The Linux Foundation, PlanetScale

Initial release

2022

2009

2004

2013

Current release

2.0, September 2019

6.0.7, June 2023

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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.

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java, Javascript

Rust

C++

Java

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

yes

schema-free, schema definition possible

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

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)

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

with proprietary extensions

APIs and other access methods

JDBC

gRPC
HTTP API
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

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C++
Erlang
Go
Java
JavaScript

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Python

JavaScript

yes

proprietary syntax

Triggers

yes

in MongoDB Atlas only

yes

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

Multi-source replication
Source-replica replication

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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

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 at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Simple rights management via user accounts

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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