DBMS > GridDB vs. Microsoft Access vs. MongoDB vs. Stardog vs. TDengine

System Properties Comparison GridDB vs. Microsoft Access vs. MongoDB vs. Stardog vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Time Series DBMS and big data platform

Primary database model

Secondary database models

Key-value store
Relational 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	2.02
Rank	#132	Overall
	#11	Time Series DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	2.68
Rank	#109	Overall
	#8	Time Series DBMS

Website

griddb.net

www.microsoft.com/en-us/microsoft-365/access

www.mongodb.com

www.stardog.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.griddb.net

developer.microsoft.com/en-us/access

www.mongodb.com/docs/manual

docs.stardog.com

docs.tdengine.com

Developer

Toshiba Corporation

Microsoft

MongoDB, Inc

Stardog-Union

TDEngine, previously Taos Data

Initial release

2013

1992

2009

2010

2019

Current release

5.1, August 2022

1902 (16.0.11328.20222), March 2019

6.0.7, June 2023

7.3.0, May 2020

3.0, August 2022

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Bundled with Microsoft Office

Open Source

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

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPL V3, also commercial editions available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

C++

Java

Server operating systems

Linux

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Solaris
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.

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

but not compliant to any SQL standard

Read-only SQL queries via the MongoDB Atlas SQL Interface

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

JDBC
RESTful HTTP API

Supported programming languages

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

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

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

JavaScript

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

since Access 2010 using the ACE-engine

yes

in MongoDB Atlas only

yes

via event handlers

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Source-replica replication

none

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

Multi-source replication in HA-Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

relationships in graphs

Transaction concepts

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

ACID at container level

ACID

but no files for transaction logging

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

optional, enabled by default

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 database

a simple user-level security was built in till version Access 2003

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

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

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

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

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

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

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

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

Market metrics

GitHub trending repository
» more

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

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

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